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Google at APS 2024

Today the 2024 March Meeting of the American Physical Society (APS) kicks off in Minneapolis, MN. A premier conference on topics ranging across physics and related fields, APS 2024 brings together researchers, students, and industry professionals to share their discoveries and build partnerships with the goal of realizing fundamental advances in physics-related sciences and technology.

This year, Google has a strong presence at APS with a booth hosted by the Google Quantum AI team, 50+ talks throughout the conference, and participation in conference organizing activities, special sessions and events. Attending APS 2024 in person? Come visit Google’s Quantum AI booth to learn more about the exciting work we’re doing to solve some of the field’s most interesting challenges.

You can learn more about the latest cutting edge work we are presenting at the conference along with our schedule of booth events below (Googlers listed in bold).

Organizing Committee

Session Chairs include: Aaron Szasz

Booth Activities

This schedule is subject to change. Please visit the Google Quantum AI booth for more information.

Presenter: Matt McEwen
Tue, Mar 5 | 11:00 AM CST

Presenter: Tanuj Khattar
Tue, Mar 5 | 2:30 PM CST

Presenter: Tanuj Khattar
Thu, Mar 7 | 11:00 AM CST

$5M XPRIZE / Google Quantum AI competition to accelerate quantum applications Q&A
Presenter: Ryan Babbush
Thu, Mar 7 | 11:00 AM CST



Certifying highly-entangled states from few single-qubit measurements
Presenter: Hsin-Yuan Huang
Author: Hsin-Yuan Huang
Session A45: New Frontiers in Machine Learning Quantum Physics

Toward high-fidelity analog quantum simulation with superconducting qubits
Presenter: Trond Andersen
Authors: Trond I Andersen, Xiao Mi, Amir H Karamlou, Nikita Astrakhantsev, Andrey Klots, Julia Berndtsson, Andre Petukhov, Dmitry Abanin, Lev B Ioffe, Yu Chen, Vadim Smelyanskiy, Pedram Roushan
Session A51: Applications on Noisy Quantum Hardware I

Measuring circuit errors in context for surface code circuits
Presenter: Dripto M Debroy
Authors: Dripto M Debroy, Jonathan A Gross, Élie Genois, Zhang Jiang
Session B50: Characterizing Noise with QCVV Techniques

Quantum computation of stopping power for inertial fusion target design I: Physics overview and the limits of classical algorithms
Presenter: Andrew D. Baczewski
Authors: Nicholas C. Rubin, Dominic W. Berry, Alina Kononov, Fionn D. Malone, Tanuj Khattar, Alec White, Joonho Lee, Hartmut Neven, Ryan Babbush, Andrew D. Baczewski
Session B51: Heterogeneous Design for Quantum Applications
Link to Paper

Quantum computation of stopping power for inertial fusion target design II: Physics overview and the limits of classical algorithms
Presenter: Nicholas C. Rubin
Authors: Nicholas C. Rubin, Dominic W. Berry, Alina Kononov, Fionn D. Malone, Tanuj Khattar, Alec White, Joonho Lee, Hartmut Neven, Ryan Babbush, Andrew D. Baczewski
Session B51: Heterogeneous Design for Quantum Applications
Link to Paper

Calibrating Superconducting Qubits: From NISQ to Fault Tolerance
Presenter: Sabrina S Hong
Author: Sabrina S Hong
Session B56: From NISQ to Fault Tolerance

Measurement and feedforward induced entanglement negativity transition
Presenter: Ramis Movassagh
Authors: Alireza Seif, Yu-Xin Wang, Ramis Movassagh, Aashish A. Clerk
Session B31: Measurement Induced Criticality in Many-Body Systems
Link to Paper

Effective quantum volume, fidelity and computational cost of noisy quantum processing experiments
Presenter: Salvatore Mandra
Authors: Kostyantyn Kechedzhi, Sergei V Isakov, Salvatore Mandra, Benjamin Villalonga, X. Mi, Sergio Boixo, Vadim Smelyanskiy
Session B52: Quantum Algorithms and Complexity
Link to Paper

Accurate thermodynamic tables for solids using Machine Learning Interaction Potentials and Covariance of Atomic Positions
Presenter: Mgcini K Phuthi
Authors: Mgcini K Phuthi, Yang Huang, Michael Widom, Ekin D Cubuk, Venkat Viswanathan
Session D60: Machine Learning of Molecules and Materials: Chemical Space and Dynamics


IN-Situ Pulse Envelope Characterization Technique (INSPECT)
Presenter: Zhang Jiang
Authors: Zhang Jiang, Jonathan A Gross, Élie Genois
Session F50: Advanced Randomized Benchmarking and Gate Calibration

Characterizing two-qubit gates with dynamical decoupling
Presenter: Jonathan A Gross
Authors: Jonathan A Gross, Zhang Jiang, Élie Genois, Dripto M Debroy, Ze-Pei Cian*, Wojciech Mruczkiewicz
Session F50: Advanced Randomized Benchmarking and Gate Calibration

Statistical physics of regression with quadratic models
Presenter: Blake Bordelon
Authors: Blake Bordelon, Cengiz Pehlevan, Yasaman Bahri
Session EE01: V: Statistical and Nonlinear Physics II

Improved state preparation for first-quantized simulation of electronic structure
Presenter: William J Huggins
Authors: William J Huggins, Oskar Leimkuhler, Torin F Stetina, Birgitta Whaley
Session G51: Hamiltonian Simulation

Controlling large superconducting quantum processors
Presenter: Paul V. Klimov
Authors: Paul V. Klimov, Andreas Bengtsson, Chris Quintana, Alexandre Bourassa, Sabrina Hong, Andrew Dunsworth, Kevin J. Satzinger, William P. Livingston, Volodymyr Sivak, Murphy Y. Niu, Trond I. Andersen, Yaxing Zhang, Desmond Chik, Zijun Chen, Charles Neill, Catherine Erickson, Alejandro Grajales Dau, Anthony Megrant, Pedram Roushan, Alexander N. Korotkov, Julian Kelly, Vadim Smelyanskiy, Yu Chen, Hartmut Neven
Session G30: Commercial Applications of Quantum Computing)
Link to Paper

Gaussian boson sampling: Determining quantum advantage
Presenter: Peter D Drummond
Authors: Peter D Drummond, Alex Dellios, Ned Goodman, Margaret D Reid, Ben Villalonga
Session G50: Quantum Characterization, Verification, and Validation II

Attention to complexity III: learning the complexity of random quantum circuit states
Presenter: Hyejin Kim
Authors: Hyejin Kim, Yiqing Zhou, Yichen Xu, Chao Wan, Jin Zhou, Yuri D Lensky, Jesse Hoke, Pedram Roushan, Kilian Q Weinberger, Eun-Ah Kim
Session G50: Quantum Characterization, Verification, and Validation II

Balanced coupling in superconducting circuits
Presenter: Daniel T Sank
Authors: Daniel T Sank, Sergei V Isakov, Mostafa Khezri, Juan Atalaya
Session K48: Strongly Driven Superconducting Systems

Resource estimation of Fault Tolerant algorithms using Qᴜᴀʟᴛʀᴀɴ
Presenter: Tanuj Khattar
Author: Tanuj Khattar
Session K49: Algorithms and Implementations on Near-Term Quantum Computers


Discovering novel quantum dynamics with superconducting qubits
Presenter: Pedram Roushan
Author: Pedram Roushan
Session M24: Analog Quantum Simulations Across Platforms

Deciphering Tumor Heterogeneity in Triple-Negative Breast Cancer: The Crucial Role of Dynamic Cell-Cell and Cell-Matrix Interactions
Presenter: Susan Leggett
Authors: Susan Leggett, Ian Wong, Celeste Nelson, Molly Brennan, Mohak Patel, Christian Franck, Sophia Martinez, Joe Tien, Lena Gamboa, Thomas Valentin, Amanda Khoo, Evelyn K Williams
Session M27: Mechanics of Cells and Tissues II

Toward implementation of protected charge-parity qubits
Presenter: Abigail Shearrow
Authors: Abigail Shearrow, Matthew Snyder, Bradley G Cole, Kenneth R Dodge, Yebin Liu, Andrey Klots, Lev B Ioffe, Britton L Plourde, Robert McDermott
Session N48: Unconventional Superconducting Qubits

Electronic capacitance in tunnel junctions for protected charge-parity qubits
Presenter: Bradley G Cole
Authors: Bradley G Cole, Kenneth R Dodge, Yebin Liu, Abigail Shearrow, Matthew Snyder, Andrey Klots, Lev B Ioffe, Robert McDermott, B.L.T. Plourde
Session N48: Unconventional Superconducting Qubits

Overcoming leakage in quantum error correction
Presenter: Kevin C. Miao
Authors: Kevin C. Miao, Matt McEwen, Juan Atalaya, Dvir Kafri, Leonid P. Pryadko, Andreas Bengtsson, Alex Opremcak, Kevin J. Satzinger, Zijun Chen, Paul V. Klimov, Chris Quintana, Rajeev Acharya, Kyle Anderson, Markus Ansmann, Frank Arute, Kunal Arya, Abraham Asfaw, Joseph C. Bardin, Alexandre Bourassa, Jenna Bovaird, Leon Brill, Bob B. Buckley, David A. Buell, Tim Burger, Brian Burkett, Nicholas Bushnell, Juan Campero, Ben Chiaro, Roberto Collins, Paul Conner, Alexander L. Crook, Ben Curtin, Dripto M. Debroy, Sean Demura, Andrew Dunsworth, Catherine Erickson, Reza Fatemi, Vinicius S. Ferreira, Leslie Flores Burgos, Ebrahim Forati, Austin G. Fowler, Brooks Foxen, Gonzalo Garcia, William Giang, Craig Gidney, Marissa Giustina, Raja Gosula, Alejandro Grajales Dau, Jonathan A. Gross, Michael C. Hamilton, Sean D. Harrington, Paula Heu, Jeremy Hilton, Markus R. Hoffmann, Sabrina Hong, Trent Huang, Ashley Huff, Justin Iveland, Evan Jeffrey, Zhang Jiang, Cody Jones, Julian Kelly, Seon Kim, Fedor Kostritsa, John Mark Kreikebaum, David Landhuis, Pavel Laptev, Lily Laws, Kenny Lee, Brian J. Lester, Alexander T. Lill, Wayne Liu, Aditya Locharla, Erik Lucero, Steven Martin, Anthony Megrant, Xiao Mi, Shirin Montazeri, Alexis Morvan, Ofer Naaman, Matthew Neeley, Charles Neill, Ani Nersisyan, Michael Newman, Jiun How Ng, Anthony Nguyen, Murray Nguyen, Rebecca Potter, Charles Rocque, Pedram Roushan, Kannan Sankaragomathi, Christopher Schuster, Michael J. Shearn, Aaron Shorter, Noah Shutty, Vladimir Shvarts, Jindra Skruzny, W. Clarke Smith, George Sterling, Marco Szalay, Douglas Thor, Alfredo Torres, Theodore White, Bryan W. K. Woo, Z. Jamie Yao, Ping Yeh, Juhwan Yoo, Grayson Young, Adam Zalcman, Ningfeng Zhu, Nicholas Zobrist, Hartmut Neven, Vadim Smelyanskiy, Andre Petukhov, Alexander N. Korotkov, Daniel Sank, Yu Chen
Session N51: Quantum Error Correction Code Performance and Implementation I
Link to Paper

Modeling the performance of the surface code with non-uniform error distribution: Part 1
Presenter: Yuri D Lensky
Authors: Yuri D Lensky, Volodymyr Sivak, Kostyantyn Kechedzhi, Igor Aleiner
Session N51: Quantum Error Correction Code Performance and Implementation I

Modeling the performance of the surface code with non-uniform error distribution: Part 2
Presenter: Volodymyr Sivak
Authors: Volodymyr Sivak, Michael Newman, Cody Jones, Henry Schurkus, Dvir Kafri, Yuri D Lensky, Paul Klimov, Kostyantyn Kechedzhi, Vadim Smelyanskiy
Session N51: Quantum Error Correction Code Performance and Implementation I

Highly optimized tensor network contractions for the simulation of classically challenging quantum computations
Presenter: Benjamin Villalonga
Author: Benjamin Villalonga
Session Q51: Co-evolution of Quantum Classical Algorithms

Teaching modern quantum computing concepts using hands-on open-source software at all levels
Presenter: Abraham Asfaw
Author: Abraham Asfaw
Session Q61: Teaching Quantum Information at All Levels II


New circuits and an open source decoder for the color code
Presenter: Craig Gidney
Authors: Craig Gidney, Cody Jones
Session S51: Quantum Error Correction Code Performance and Implementation II
Link to Paper

Performing Hartree-Fock many-body physics calculations with large language models
Presenter: Eun-Ah Kim
Authors: Eun-Ah Kim, Haining Pan, Nayantara Mudur, William Taranto, Subhashini Venugopalan, Yasaman Bahri, Michael P Brenner
Session S18: Data Science, AI and Machine Learning in Physics I

New methods for reducing resource overhead in the surface code
Presenter: Michael Newman
Authors: Craig M Gidney, Michael Newman, Peter Brooks, Cody Jones
Session S51: Quantum Error Correction Code Performance and Implementation II
Link to Paper

Challenges and opportunities for applying quantum computers to drug design
Presenter: Raffaele Santagati
Authors: Raffaele Santagati, Alan Aspuru-Guzik, Ryan Babbush, Matthias Degroote, Leticia Gonzalez, Elica Kyoseva, Nikolaj Moll, Markus Oppel, Robert M. Parrish, Nicholas C. Rubin, Michael Streif, Christofer S. Tautermann, Horst Weiss, Nathan Wiebe, Clemens Utschig-Utschig
Session S49: Advances in Quantum Algorithms for Near-Term Applications
Link to Paper

Dispatches from Google's hunt for super-quadratic quantum advantage in new applications
Presenter: Ryan Babbush
Author: Ryan Babbush
Session T45: Recent Advances in Quantum Algorithms

Qubit as a reflectometer
Presenter: Yaxing Zhang
Authors: Yaxing Zhang, Benjamin Chiaro
Session T48: Superconducting Fabrication, Packaging, & Validation

Random-matrix theory of measurement-induced phase transitions in nonlocal Floquet quantum circuits
Presenter: Aleksei Khindanov
Authors: Aleksei Khindanov, Lara Faoro, Lev Ioffe, Igor Aleiner
Session W14: Measurement-Induced Phase Transitions

Continuum limit of finite density many-body ground states with MERA
Presenter: Subhayan Sahu
Authors: Subhayan Sahu, Guifré Vidal
Session W58: Extreme-Scale Computational Science Discovery in Fluid Dynamics and Related Disciplines II

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain
Presenter: Eliott Rosenberg
Authors: Eliott Rosenberg, Trond Andersen, Rhine Samajdar, Andre Petukhov, Jesse Hoke*, Dmitry Abanin, Andreas Bengtsson, Ilya Drozdov, Catherine Erickson, Paul Klimov, Xiao Mi, Alexis Morvan, Matthew Neeley, Charles Neill, Rajeev Acharya, Richard Allen, Kyle Anderson, Markus Ansmann, Frank Arute, Kunal Arya, Abraham Asfaw, Juan Atalaya, Joseph Bardin, A. Bilmes, Gina Bortoli, Alexandre Bourassa, Jenna Bovaird, Leon Brill, Michael Broughton, Bob B. Buckley, David Buell, Tim Burger, Brian Burkett, Nicholas Bushnell, Juan Campero, Hung-Shen Chang, Zijun Chen, Benjamin Chiaro, Desmond Chik, Josh Cogan, Roberto Collins, Paul Conner, William Courtney, Alexander Crook, Ben Curtin, Dripto Debroy, Alexander Del Toro Barba, Sean Demura, Agustin Di Paolo, Andrew Dunsworth, Clint Earle, E. Farhi, Reza Fatemi, Vinicius Ferreira, Leslie Flores, Ebrahim Forati, Austin Fowler, Brooks Foxen, Gonzalo Garcia, Élie Genois, William Giang, Craig Gidney, Dar Gilboa, Marissa Giustina, Raja Gosula, Alejandro Grajales Dau, Jonathan Gross, Steve Habegger, Michael Hamilton, Monica Hansen, Matthew Harrigan, Sean Harrington, Paula Heu, Gordon Hill, Markus Hoffmann, Sabrina Hong, Trent Huang, Ashley Huff, William Huggins, Lev Ioffe, Sergei Isakov, Justin Iveland, Evan Jeffrey, Zhang Jiang, Cody Jones, Pavol Juhas, D. Kafri, Tanuj Khattar, Mostafa Khezri, Mária Kieferová, Seon Kim, Alexei Kitaev, Andrey Klots, Alexander Korotkov, Fedor Kostritsa, John Mark Kreikebaum, David Landhuis, Pavel Laptev, Kim Ming Lau, Lily Laws, Joonho Lee, Kenneth Lee, Yuri Lensky, Brian Lester, Alexander Lill, Wayne Liu, William P. Livingston, A. Locharla, Salvatore Mandrà, Orion Martin, Steven Martin, Jarrod McClean, Matthew McEwen, Seneca Meeks, Kevin Miao, Amanda Mieszala, Shirin Montazeri, Ramis Movassagh, Wojciech Mruczkiewicz, Ani Nersisyan, Michael Newman, Jiun How Ng, Anthony Nguyen, Murray Nguyen, M. Niu, Thomas O'Brien, Seun Omonije, Alex Opremcak, Rebecca Potter, Leonid Pryadko, Chris Quintana, David Rhodes, Charles Rocque, N. Rubin, Negar Saei, Daniel Sank, Kannan Sankaragomathi, Kevin Satzinger, Henry Schurkus, Christopher Schuster, Michael Shearn, Aaron Shorter, Noah Shutty, Vladimir Shvarts, Volodymyr Sivak, Jindra Skruzny, Clarke Smith, Rolando Somma, George Sterling, Doug Strain, Marco Szalay, Douglas Thor, Alfredo Torres, Guifre Vidal, Benjamin Villalonga, Catherine Vollgraff Heidweiller, Theodore White, Bryan Woo, Cheng Xing, Jamie Yao, Ping Yeh, Juhwan Yoo, Grayson Young, Adam Zalcman, Yaxing Zhang, Ningfeng Zhu, Nicholas Zobrist, Hartmut Neven, Ryan Babbush, Dave Bacon, Sergio Boixo, Jeremy Hilton, Erik Lucero, Anthony Megrant, Julian Kelly, Yu Chen, Vadim Smelyanskiy, Vedika Khemani, Sarang Gopalakrishnan, Tomaž Prosen, Pedram Roushan
Session W50: Quantum Simulation of Many-Body Physics
Link to Paper

The fast multipole method on a quantum computer
Presenter: Kianna Wan
Authors: Kianna Wan, Dominic W Berry, Ryan Babbush
Session W50: Quantum Simulation of Many-Body Physics


The quantum computing industry and protecting national security: what tools will work?
Presenter: Kate Weber
Author: Kate Weber
Session Y43: Industry, Innovation, and National Security: Finding the Right Balance

Novel charging effects in the fluxonium qubit
Presenter: Agustin Di Paolo
Authors: Agustin Di Paolo, Kyle Serniak, Andrew J Kerman, William D Oliver
Session Y46: Fluxonium-Based Superconducting Quibits

Microwave Engineering of Parametric Interactions in Superconducting Circuits
Presenter: Ofer Naaman
Author: Ofer Naaman
Session Z46: Broadband Parametric Amplifiers and Circulators

Linear spin wave theory of large magnetic unit cells using the Kernel Polynomial Method
Presenter: Harry Lane
Authors: Harry Lane, Hao Zhang, David A Dahlbom, Sam Quinn, Rolando D Somma, Martin P Mourigal, Cristian D Batista, Kipton Barros
Session Z62: Cooperative Phenomena, Theory

*Work done while at Google

Source: Google AI Blog

Google at EMNLP 2023

Google is proud to be a Diamond Sponsor of Empirical Methods in Natural Language Processing (EMNLP 2023), a premier annual conference, which is being held this week in Sentosa, Singapore. Google has a strong presence at this year’s conference with over 65 accepted papers and active involvement in 11 workshops and tutorials. Google is also happy to be a Major Sponsor for the Widening NLP workshop (WiNLP), which aims to highlight global representations of people, perspectives, and cultures in AI and ML. We look forward to sharing some of our extensive NLP research and expanding our partnership with the broader research community.

We hope you’ll visit the Google booth to chat with researchers who are actively pursuing the latest innovations in NLP, and check out some of the scheduled booth activities (e.g., demos and Q&A sessions listed below). Visit the @GoogleAI X (Twitter) and LinkedIn accounts to find out more about the Google booth activities at EMNLP 2023.

Take a look below to learn more about the Google research being presented at EMNLP 2023 (Google affiliations in bold).

Board & Organizing Committee

Sponsorship Chair: Shyam Upadyay
Industry Track Chair: Imed Zitouni
Senior Program Committee: Roee Aharoni, Annie Louis, Vinodkumar Prabhakaran, Shruti Rijhwani, Brian Roark, Partha Talukdar

Google Research booth activities

This schedule is subject to change. Please visit the Google booth for more information.

Developing and Utilizing Evaluation Metrics for Machine Translation & Improving Multilingual NLP
Presenter: Isaac Caswell, Dan Deutch, Jan-Thorsten Peter, David Vilar Torres
Fri, Dec 8 | 10:30AM -11:00AM SST

Differentiable Search Indexes & Generative Retrieval
Presenter: Sanket Vaibhav Mehta, Vinh Tran, Kai Hui, Ronak Pradeep*
Fri, Dec 8 | 3:30PM -4:00PM SST

Retrieval and Generation in a single pass
Presenter: Palak Jain, Livio Baldini Soares
Sat, Dec 9 | 10:30AM -11:00AM SST

Amplifying Adversarial Attacks
Presenter: Anu Sinha
Sat, Dec 9 | 12:30PM -1:45PM SST

Automate prompt design: Universal Self-Adaptive Prompting (see blog post)
Presenter: Xingchen Qian*, Ruoxi Sun
Sat, Dec 9 | 3:30PM -4:00PM SST


SynJax: Structured Probability Distributions for JAX
Miloš Stanojević, Laurent Sartran

Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning
Clifton Poth, Hannah Sterz, Indraneil Paul, Sukannya Purkayastha, Leon Engländer, Timo Imhof, Ivan Vulić, Sebastian Ruder, Iryna Gurevych, Jonas Pfeiffer

DocumentNet: Bridging the Data Gap in Document Pre-training
Lijun Yu, Jin Miao, Xiaoyu Sun, Jiayi Chen, Alexander Hauptmann, Hanjun Dai, Wei Wei

AART: AI-Assisted Red-Teaming with Diverse Data Generation for New LLM-Powered Applications
Bhaktipriya Radharapu, Kevin Robinson, Lora Aroyo, Preethi Lahoti

CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks
Mete Ismayilzada, Debjit Paul, Syrielle Montariol, Mor Geva, Antoine Bosselut

Large Language Models Can Self-Improve
Jiaxin Huang*, Shixiang Shane Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han

Dissecting Recall of Factual Associations in Auto-Regressive Language Models
Mor Geva, Jasmijn Bastings, Katja Filippova, Amir Globerson

Stop Uploading Test Data in Plain Text: Practical Strategies for Mitigating Data Contamination by Evaluation Benchmarks
Alon Jacovi, Avi Caciularu, Omer Goldman, Yoav Goldberg

Selective Labeling: How to Radically Lower Data-Labeling Costs for Document Extraction Models
Yichao Zhou, James Bradley Wendt, Navneet Potti, Jing Xie, Sandeep Tata

Measuring Attribution in Natural Language Generation Models
Hannah Rashkin, Vitaly Nikolaev, Matthew Lamm, Lora Aroyo, Michael Collins, Dipanjan Das, Slav Petrov, Gaurav Singh Tomar, Iulia Turc, David Reitter

Inverse Scaling Can Become U-Shaped
Jason Wei*, Najoung Kim, Yi Tay*, Quoc Le

INSTRUCTSCORE: Towards Explainable Text Generation Evaluation with Automatic Feedback
Wenda Xu, Danqing Wang, Liangming Pan, Zhenqiao Song, Markus Freitag, William Yang Wang, Lei Li

On the Robustness of Dialogue History Representation in Conversational Question Answering: A Comprehensive Study and a New Prompt-Based Method
Zorik Gekhman, Nadav Oved, Orgad Keller, Idan Szpektor, Roi Reichart

Investigating Efficiently Extending Transformers for Long-Input Summarization
Jason Phang*, Yao Zhao, Peter J Liu

DSI++: Updating Transformer Memory with New Documents
Sanket Vaibhav Mehta*, Jai Gupta, Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Jinfeng Rao, Marc Najork, Emma Strubell, Donald Metzler

MultiTurnCleanup: A Benchmark for Multi-Turn Spoken Conversational Transcript Cleanup
Hua Shen*, Vicky Zayats, Johann C Rocholl, Daniel David Walker, Dirk Padfield

Findings of EMNLP

Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs
Jiefeng Chen*, Jinsung Yoon, Sayna Ebrahimi, Sercan O Arik, Tomas Pfister, Somesh Jha

A Comprehensive Evaluation of Tool-Assisted Generation Strategies
Alon Jacovi*, Avi Caciularu, Jonathan Herzig, Roee Aharoni, Bernd Bohnet, Mor Geva

1-PAGER: One Pass Answer Generation and Evidence Retrieval
Palak Jain, Livio Baldini Soares, Tom Kwiatkowski

MaXM: Towards Multilingual Visual Question Answering
Soravit Changpinyo, Linting Xue, Michal Yarom, Ashish V. Thapliyal, Idan Szpektor, Julien Amelot, Xi Chen, Radu Soricut

SDOH-NLI: A Dataset for Inferring Social Determinants of Health from Clinical Notes
Adam D. Lelkes, Eric Loreaux*, Tal Schuster, Ming-Jun Chen, Alvin Rajkomar

Machine Reading Comprehension Using Case-based Reasoning
Dung Ngoc Thai, Dhruv Agarwal, Mudit Chaudhary, Wenlong Zhao, Rajarshi Das, Jay-Yoon Lee, Hannaneh Hajishirzi, Manzil Zaheer, Andrew McCallum

Cross-lingual Open-Retrieval Question Answering for African Languages
Odunayo Ogundepo, Tajuddeen Gwadabe, Clara E. Rivera, Jonathan H. Clark, Sebastian Ruder, David Ifeoluwa Adelani, Bonaventure F. P. Dossou, Abdou Aziz DIOP, Claytone Sikasote, Gilles HACHEME, Happy Buzaaba, Ignatius Ezeani, Rooweither Mabuya, Salomey Osei, Chris Chinenye Emezue, Albert Kahira, Shamsuddeen Hassan Muhammad, Akintunde Oladipo, Abraham Toluwase Owodunni, Atnafu Lambebo Tonja, Iyanuoluwa Shode, Akari Asai, Anuoluwapo Aremu, Ayodele Awokoya, Bernard Opoku, Chiamaka Ijeoma Chukwuneke, Christine Mwase, Clemencia Siro, Stephen Arthur, Tunde Oluwaseyi Ajayi, Verrah Akinyi Otiende, Andre Niyongabo Rubungo, Boyd Sinkala, Daniel Ajisafe, Emeka Felix Onwuegbuzia, Falalu Ibrahim Lawan, Ibrahim Said Ahmad, Jesujoba Oluwadara Alabi, CHINEDU EMMANUEL MBONU, Mofetoluwa Adeyemi, Mofya Phiri, Orevaoghene Ahia, Ruqayya Nasir Iro, Sonia Adhiambo

On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study
Polina Zablotskaia, Du Phan, Joshua Maynez, Shashi Narayan, Jie Ren, Jeremiah Zhe Liu

Epsilon Sampling Rocks: Investigating Sampling Strategies for Minimum Bayes Risk Decoding for Machine Translation
Markus Freitag, Behrooz Ghorbani*, Patrick Fernandes*

Sources of Hallucination by Large Language Models on Inference Tasks
Nick McKenna, Tianyi Li, Liang Cheng, Mohammad Javad Hosseini, Mark Johnson, Mark Steedman

Don’t Add, Don’t Miss: Effective Content Preserving Generation from Pre-selected Text Spans
Aviv Slobodkin, Avi Caciularu, Eran Hirsch, Ido Dagan

What Makes Chain-of-Thought Prompting Effective? A Counterfactual Study
Aman Madaan*, Katherine Hermann, Amir Yazdanbakhsh

Understanding HTML with Large Language Models
Izzeddin Gur, Ofir Nachum, Yingjie Miao, Mustafa Safdari, Austin Huang, Aakanksha Chowdhery, Sharan Narang, Noah Fiedel, Aleksandra Faust

Improving the Robustness of Summarization Models by Detecting and Removing Input Noise
Kundan Krishna*, Yao Zhao, Jie Ren, Balaji Lakshminarayanan, Jiaming Luo, Mohammad Saleh, Peter J. Liu

In-Context Learning Creates Task Vectors
Roee Hendel, Mor Geva, Amir Globerson

Pre-training Without Attention
Junxiong Wang, Jing Nathan Yan, Albert Gu, Alexander M Rush

MUX-PLMs: Data Multiplexing for High-Throughput Language Models
Vishvak Murahari, Ameet Deshpande, Carlos E Jimenez, Izhak Shafran, Mingqiu Wang, Yuan Cao, Karthik R Narasimhan

PaRaDe: Passage Ranking Using Demonstrations with LLMs
Andrew Drozdov*, Honglei Zhuang, Zhuyun Dai, Zhen Qin, Razieh Rahimi, Xuanhui Wang, Dana Alon, Mohit Iyyer, Andrew McCallum, Donald Metzler*, Kai Hui

Long-Form Speech Translation Through Segmentation with Finite-State Decoding Constraints on Large Language Models
Arya D. McCarthy, Hao Zhang, Shankar Kumar, Felix Stahlberg, Ke Wu

Unsupervised Opinion Summarization Using Approximate Geodesics
Somnath Basu Roy Chowdhury*, Nicholas Monath, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi

SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data
Ruoxi Sun, Sercan O. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister

Retrieval-Augmented Parsing for Complex Graphs by Exploiting Structure and Uncertainty
Zi Lin, Quan Yuan, Panupong Pasupat, Jeremiah Zhe Liu, Jingbo Shang

A Zero-Shot Language Agent for Computer Control with Structured Reflection
Tao Li, Gang Li, Zhiwei Deng, Bryan Wang*, Yang Li

Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches
Daniel Fried, Nicholas Tomlin, Jennifer Hu, Roma Patel, Aida Nematzadeh

Improving Classifier Robustness Through Active Generation of Pairwise Counterfactuals
Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Jilin Chen, Ed H. Chi, Alex Beutel

mmT5: Modular Multilingual Pre-training Solves Source Language Hallucinations
Jonas Pfeiffer, Francesco Piccinno, Massimo Nicosia, Xinyi Wang, Machel Reid, Sebastian Ruder

Scaling Laws vs Model Architectures: How Does Inductive Bias Influence Scaling?
Yi Tay, Mostafa Dehghani, Samira Abnar, Hyung Won Chung, William Fedus, Jinfeng Rao, Sharan Narang, Vinh Q. Tran, Dani Yogatama, Donald Metzler

TaTA: A Multilingual Table-to-Text Dataset for African Languages
Sebastian Gehrmann, Sebastian Ruder, Vitaly Nikolaev, Jan A. Botha, Michael Chavinda, Ankur P Parikh, Clara E. Rivera

XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages
Sebastian Ruder, Jonathan H. Clark, Alexander Gutkin, Mihir Kale, Min Ma, Massimo Nicosia, Shruti Rijhwani, Parker Riley, Jean Michel Amath Sarr, Xinyi Wang, John Frederick Wieting, Nitish Gupta, Anna Katanova, Christo Kirov, Dana L Dickinson, Brian Roark, Bidisha Samanta, Connie Tao, David Ifeoluwa Adelani, Vera Axelrod, Isaac Rayburn Caswell, Colin Cherry, Dan Garrette, Reeve Ingle, Melvin Johnson, Dmitry Panteleev, Partha Talukdar

q2d: Turning Questions into Dialogs to Teach Models How to Search
Yonatan Bitton, Shlomi Cohen-Ganor, Ido Hakimi, Yoad Lewenberg, Roee Aharoni, Enav Weinreb

Emergence of Abstract State Representations in Embodied Sequence Modeling
Tian Yun*, Zilai Zeng, Kunal Handa, Ashish V Thapliyal, Bo Pang, Ellie Pavlick, Chen Sun

Evaluating and Modeling Attribution for Cross-Lingual Question Answering
Benjamin Muller*, John Wieting, Jonathan H. Clark, Tom Kwiatkowski, Sebastian Ruder, Livio Baldini Soares, Roee Aharoni, Jonathan Herzig, Xinyi Wang

Weakly-Supervised Learning of Visual Relations in Multimodal Pre-training
Emanuele Bugliarello, Aida Nematzadeh, Lisa Anne Hendricks

How Do Languages Influence Each Other? Studying Cross-Lingual Data Sharing During LM Fine-Tuning
Rochelle Choenni, Dan Garrette, Ekaterina Shutova

CompoundPiece: Evaluating and Improving Decompounding Performance of Language Models
Benjamin Minixhofer, Jonas Pfeiffer, Ivan Vulić

IC3: Image Captioning by Committee Consensus
David Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A Ross, John Canny

The Curious Case of Hallucinatory (Un)answerability: Finding Truths in the Hidden States of Over-Confident Large Language Models
Aviv Slobodkin, Omer Goldman, Avi Caciularu, Ido Dagan, Shauli Ravfogel

Evaluating Large Language Models on Controlled Generation Tasks
Jiao Sun, Yufei Tian, Wangchunshu Zhou, Nan Xu, Qian Hu, Rahul Gupta, John Wieting, Nanyun Peng, Xuezhe Ma

Ties Matter: Meta-Evaluating Modern Metrics with Pairwise Accuracy and Tie Calibration
Daniel Deutsch, George Foster, Markus Freitag

Transcending Scaling Laws with 0.1% Extra Compute
Yi Tay*, Jason Wei*, Hyung Won Chung*, Vinh Q. Tran, David R. So*, Siamak Shakeri, Xavier Garcia, Huaixiu Steven Zheng, Jinfeng Rao, Aakanksha Chowdhery, Denny Zhou, Donald Metzler, Slav Petrov, Neil Houlsby, Quoc V. Le, Mostafa Dehghani

Data Similarity is Not Enough to Explain Language Model Performance
Gregory Yauney*, Emily Reif, David Mimno

Self-Influence Guided Data Reweighting for Language Model Pre-training
Megh Thakkar*, Tolga Bolukbasi, Sriram Ganapathy, Shikhar Vashishth, Sarath Chandar, Partha Talukdar

ReTAG: Reasoning Aware Table to Analytic Text Generation
Deepanway Ghosal, Preksha Nema, Aravindan Raghuveer

GATITOS: Using a New Multilingual Lexicon for Low-Resource Machine Translation
Alex Jones*, Isaac Caswell, Ishank Saxena

Video-Helpful Multimodal Machine Translation
Yihang Li, Shuichiro Shimizu, Chenhui Chu, Sadao Kurohashi, Wei Li

Symbol Tuning Improves In-Context Learning in Language Models
Jerry Wei*, Le Hou, Andrew Kyle Lampinen, Xiangning Chen*, Da Huang, Yi Tay*, Xinyun Chen, Yifeng Lu, Denny Zhou, Tengyu Ma*, Quoc V Le

"Don't Take This Out of Context!" On the Need for Contextual Models and Evaluations for Stylistic Rewriting
Akhila Yerukola, Xuhui Zhou, Elizabeth Clark, Maarten Sap

QAmeleon: Multilingual QA with Only 5 Examples
Priyanka Agrawal, Chris Alberti, Fantine Huot, Joshua Maynez, Ji Ma, Sebastian Ruder, Kuzman Ganchev, Dipanjan Das, Mirella Lapata

Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision
Eugene Kharitonov, Damien Vincent, Zalán Borsos, Raphaël Marinier, Sertan Girgin, Olivier Pietquin, Matt Sharifi, Marco Tagliasacchi, Neil Zeghidour

AnyTOD: A Programmable Task-Oriented Dialog System
Jeffrey Zhao, Yuan Cao, Raghav Gupta, Harrison Lee, Abhinav Rastogi, Mingqiu Wang, Hagen Soltau, Izhak Shafran, Yonghui Wu

Selectively Answering Ambiguous Questions
Jeremy R. Cole, Michael JQ Zhang, Daniel Gillick, Julian Martin Eisenschlos, Bhuwan Dhingra, Jacob Eisenstein

PRESTO: A Multilingual Dataset for Parsing Realistic Task-Oriented Dialogs (see blog post)
Rahul Goel, Waleed Ammar, Aditya Gupta, Siddharth Vashishtha, Motoki Sano, Faiz Surani*, Max Chang, HyunJeong Choe, David Greene, Chuan He, Rattima Nitisaroj, Anna Trukhina, Shachi Paul, Pararth Shah, Rushin Shah, Zhou Yu

LM vs LM: Detecting Factual Errors via Cross Examination
Roi Cohen, May Hamri, Mor Geva, Amir Globerson

A Suite of Generative Tasks for Multi-Level Multimodal Webpage Understanding
Andrea Burns*, Krishna Srinivasan, Joshua Ainslie, Geoff Brown, Bryan A. Plummer, Kate Saenko, Jianmo Ni, Mandy Guo

AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages
Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Abinew Ali Ayele, Nedjma Ousidhoum, David Ifeoluwa Adelani, Seid Muhie Yimam, Ibrahim Said Ahmad, Meriem Beloucif, Saif M. Mohammad, Sebastian Ruder, Oumaima Hourrane, Alipio Jorge, Pavel Brazdil, Felermino D. M. A. Ali, Davis David, Salomey Osei, Bello Shehu-Bello, Falalu Ibrahim Lawan, Tajuddeen Gwadabe, Samuel Rutunda, Tadesse Destaw Belay, Wendimu Baye Messelle, Hailu Beshada Balcha, Sisay Adugna Chala, Hagos Tesfahun Gebremichael, Bernard Opoku, Stephen Arthur

Optimizing Retrieval-Augmented Reader Models via Token Elimination
Moshe Berchansky, Peter Izsak, Avi Caciularu, Ido Dagan, Moshe Wasserblat

SEAHORSE: A Multilingual, Multifaceted Dataset for Summarization Evaluation
Elizabeth Clark, Shruti Rijhwani, Sebastian Gehrmann, Joshua Maynez, Roee Aharoni, Vitaly Nikolaev, Thibault Sellam, Aditya Siddhant, Dipanjan Das, Ankur P Parikh

GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints
Joshua Ainslie, James Lee-Thorp, Michiel de Jong*, Yury Zemlyanskiy, Federico Lebron, Sumit Sanghai

CoLT5: Faster Long-Range Transformers with Conditional Computation
Joshua Ainslie, Tao Lei, Michiel de Jong, Santiago Ontanon, Siddhartha Brahma, Yury Zemlyanskiy, David Uthus, Mandy Guo, James Lee-Thorp, Yi Tay, Yun-Hsuan Sung, Sumit Sanghai

Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting
Preethi Lahoti, Nicholas Blumm, Xiao Ma, Raghavendra Kotikalapudi, Sahitya Potluri, Qijun Tan, Hansa Srinivasan, Ben Packer, Ahmad Beirami, Alex Beutel, Jilin Chen

Universal Self-Adaptive Prompting (see blog post)
Xingchen Wan*, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Martin Eisenschlos, Sercan O. Arik, Tomas Pfister

TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models
Zorik Gekhman, Jonathan Herzig, Roee Aharoni, Chen Elkind, Idan Szpektor

Hierarchical Pre-training on Multimodal Electronic Health Records
Xiaochen Wang, Junyu Luo, Jiaqi Wang, Ziyi Yin, Suhan Cui, Yuan Zhong, Yaqing Wang, Fenglong Ma

NAIL: Lexical Retrieval Indices with Efficient Non-Autoregressive Decoders
Livio Baldini Soares, Daniel Gillick, Jeremy R. Cole, Tom Kwiatkowski

How Does Generative Retrieval Scale to Millions of Passages?
Ronak Pradeep*, Kai Hui, Jai Gupta, Adam D. Lelkes, Honglei Zhuang, Jimmy Lin, Donald Metzler, Vinh Q. Tran

Make Every Example Count: On the Stability and Utility of Self-Influence for Learning from Noisy NLP Datasets
Irina Bejan*, Artem Sokolov, Katja Filippova


The Seventh Widening NLP Workshop (WiNLP)
Major Sponsor
Organizers: Sunipa Dev
Panelist: Preethi Lahoti

The Sixth Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC)
Invited Speaker: Bernd Bohnet

The 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS)
Organizer: Geeticka Chauhan

Combined Workshop on Spatial Language Understanding and Grounded Communication for Robotics (SpLU-RoboNLP)
Invited Speaker: Andy Zeng

Natural Language Generation, Evaluation, and Metric (GEM)
Organizer: Elizabeth Clark

The First Arabic Natural Language Processing Conference (ArabicNLP)
Organizer: Imed Zitouni

The Big Picture: Crafting a Research Narrative (BigPicture)
Organizer: Nora Kassner, Sebastian Ruder

BlackboxNLP 2023: The 6th Workshop on Analysing and Interpreting Neural Networks for NLP
Organizer: Najoung Kim
Panelist: Neel Nanda

The SIGNLL Conference on Computational Natural Language Learning (CoNLL)
Co-Chair: David Reitter
Areas and ACs: Kyle Gorman (Speech and Phonology), Fei Liu (Natural Language Generation)

The Third Workshop on Multi-lingual Representation Learning (MRL)
Organizer: Omer Goldman, Sebastian Ruder
Invited Speaker: Orhan Firat


Creative Natural Language Generation
Organizer: Tuhin Chakrabarty*

* Work done while at Google

Source: Google AI Blog

Google at ICCV 2023

Google is proud to be a Platinum Sponsor of the International Conference on Computer Vision (ICCV 2023), a premier annual conference, which is being held this week in Paris, France. As a leader in computer vision research, Google has a strong presence at this year’s conference with 60 accepted papers and active involvement in 27 workshops and tutorials. Google is also proud to be a Platinum Sponsor for the LatinX in CV workshop. We look forward to sharing some of our extensive computer vision research and expanding our partnership with the broader research community.

Attending ICCV 2023? We hope you’ll visit the Google booth to chat with researchers who are actively pursuing the latest innovations in computer vision, and check out some of the scheduled booth activities (e.g., demos and Q&A sessions listed below). Visit the @GoogleAI Twitter account to find out more about the Google booth activities at ICCV 2023.

Take a look below to learn more about the Google research being presented at ICCV 2023 (Google affiliations in bold).

Board and Organizing Committee

General Chair: Cordelia Schmid
Finance Chair: Ramin Zabih
Industrial Relations Chair: Rahul Sukthankar
Publicity and Social Media Co-Chair: Boqing Gong

Google Research booth activities

Title: ImagenThings: Instant Personalized Image-to-Image Generation
Presenters: Xuhui Jia, Suraj Kothawade
Wednesday, October 4th at 12:30 PM CEST

Title: Open Images V7 (paper, dataset, blog post)
Presenters: Rodrigo Benenson, Jasper Uijlings, Jordi Pont-Tuset
Wednesday, October 4th at 3:30 PM CEST

Title: AI4Design (paper)
Presenters: Andrew Marmon, Peggy Chi, C.K. Ng
Thursday, October 5th at 10:30 AM CEST

Title: Preface: A Data-driven Volumetric Prior for Few-shot Ultra High-resolution Face Synthesis
Presenters: Marcel Bühler, Kripasindhu Sarkar
Thursday, October 5th at 12:30 PM CEST

Title: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images
Presenters: Yonatan Bitton
Thursday, October 5th at 1:00 PM CEST

Title: Image Search in Fact Check Explorer (blog post)
Presenters: Yair Alon, Avneesh Sud
Thursday, October 5th at 3:30 PM CEST

Title: UnLoc: A Unified Framework for Video Localization Tasks (paper)
Presenters: Arsha Nagrani, Xuehan Xiong
Friday, October 6th at 10:30 AM CEST

Title: Prompt-Tuning Latent Diffusion Models for Inverse Problems
Presenters: Hyungjin Chung
Friday, October 6th at 12:30 PM CEST

Title: Neural Implicit Representations for Real World Applications
Presenters: Federico Tombari, Fabian Manhardt, Marie-Julie Rakotosaona
Friday, October 6th at 3:30 PM CEST

Accepted papers

Multi-Modal Neural Radiance Field for Monocular Dense SLAM with a Light-Weight ToF Sensor
Xinyang Liu, Yijin Li, Yanbin Teng, Hujun Bao, Guofeng Zhang, Yinda Zhang, Zhaopeng Cui

ITI-GEN: Inclusive Text-to-Image Generation
Cheng Zhang, Xuanbai Chen, Siqi Chai, Chen Henry Wu, Dmitry Lagun, Thabo Beeler, Fernando De la Torre

ASIC: Aligning Sparse in-the-wild Image Collections
Kamal Gupta, Varun Jampani, Carlos Esteves, Abhinav Shrivastava, Ameesh Makadia, Noah Snavely, Abhishek Kar

VQ3D: Learning a 3D-Aware Generative Model on ImageNet
Kyle Sargent, Jing Yu Koh, Han Zhang, Huiwen Chang, Charles Herrmann, Pratul Srinivasan, Jiajun Wu, Deqing Sun

Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities
Hexiang Hu, Yi Luan, Yang Chen*, Urvashi Khandelwal, Mandar Joshi, Kenton Lee, Kristina Toutanova, Ming-Wei Chang

Sigmoid Loss for Language Image Pre-training
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, Lucas Beyer

Tracking Everything Everywhere All at Once
Qianqian Wang, Yen-Yu Chang, Ruojin Cai, Zhengqi Li, Bharath Hariharan, Aleksander Holynski, Noah Snavely

Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields
Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, Peter Hedman

Delta Denoising Score
Amir Hertz*, Kfir Aberman, Daniel Cohen-Or*

DreamBooth3D: Subject-Driven Text-to-3D Generation
Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer, Nataniel Ruiz, Ben Mildenhall, Shiran Zada, Kfir Aberman, Michael Rubinstein, Jonathan Barron, Yuanzhen Li, Varun Jampani

Encyclopedic VQA: Visual Questions about Detailed Properties of Fine-grained Categories
Thomas Mensink, Jasper Uijlings, Lluis Castrejon, Arushi Goel*, Felipe Cadar*, Howard Zhou, Fei Sha, André Araujo, Vittorio Ferrari

GECCO: Geometrically-Conditioned Point Diffusion Models
Michał J. Tyszkiewicz, Pascal Fua, Eduard Trulls

Learning from Semantic Alignment between Unpaired Multiviews for Egocentric Video Recognition
Qitong Wang, Long Zhao, Liangzhe Yuan, Ting Liu, Xi Peng

Neural Microfacet Fields for Inverse Rendering
Alexander Mai, Dor Verbin, Falko Kuester, Sara Fridovich-Keil

Rosetta Neurons: Mining the Common Units in a Model Zoo
Amil Dravid, Yossi Gandelsman, Alexei A. Efros, Assaf Shocher

Teaching CLIP to Count to Ten
Roni Paiss*, Ariel Ephrat, Omer Tov, Shiran Zada, Inbar Mosseri, Michal Irani, Tali Dekel

Vox-E: Text-guided Voxel Editing of 3D Objects
Etai Sella, Gal Fiebelman, Peter Hedman, Hadar Averbuch-Elor

CC3D: Layout-Conditioned Generation of Compositional 3D Scenes
Sherwin Bahmani, Jeong Joon Park, Despoina Paschalidou, Xingguang Yan, Gordon Wetzstein, Leonidas Guibas, Andrea Tagliasacchi

Delving into Motion-Aware Matching for Monocular 3D Object Tracking
Kuan-Chih Huang, Ming-Hsuan Yang, Yi-Hsuan Tsai

Generative Multiplane Neural Radiance for 3D-Aware Image Generation
Amandeep Kumar, Ankan Kumar Bhunia, Sanath Narayan, Hisham Cholakkal, Rao Muhammad Anwer, Salman Khan, Ming-Hsuan Yang, Fahad Shahbaz Khan

M2T: Masking Transformers Twice for Faster Decoding
Fabian Mentzer, Eirikur Agustsson, Michael Tschannen

MULLER: Multilayer Laplacian Resizer for Vision
Zhengzhong Tu, Peyman Milanfar, Hossein Talebi

SVDiff: Compact Parameter Space for Diffusion Fine-Tuning
Ligong Han*, Yinxiao Li, Han Zhang, Peyman Milanfar, Dimitris Metaxas, Feng Yang

Towards Authentic Face Restoration with Iterative Diffusion Models and Beyond
Yang Zhao, Tingbo Hou, Yu-Chuan Su, Xuhui Jia, Yandong Li, Matthias Grundmann

Unified Visual Relationship Detection with Vision and Language Models
Long Zhao, Liangzhe Yuan, Boqing Gong, Yin Cui, Florian Schroff, Ming-Hsuan Yang, Hartwig Adam, Ting Liu

3D Motion Magnification: Visualizing Subtle Motions from Time-Varying Radiance Fields
Brandon Y. Feng, Hadi Alzayer, Michael Rubinstein, William T. Freeman, Jia-Bin Huang

Global Features are All You Need for Image Retrieval and Reranking
Shihao Shao, Kaifeng Chen, Arjun Karpur, Qinghua Cui, André Araujo, Bingyi Cao

Introducing Language Guidance in Prompt-Based Continual Learning
Muhammad Gul Zain Ali Khan, Muhammad Ferjad Naeem, Luc Van Gool, Didier Stricker, Federico Tombari, Muhammad Zeshan Afzal

Multiscale Structure Guided Diffusion for Image Deblurring
Mengwei Ren*, Mauricio Delbracio, Hossein Talebi, Guido Gerig, Peyman Milanfar

Robust Monocular Depth Estimation under Challenging Conditions
Stefano Gasperini, Nils Morbitzer, HyunJun Jung, Nassir Navab, Federico Tombari

Score-Based Diffusion Models as Principled Priors for Inverse Imaging
Berthy T. Feng*, Jamie Smith, Michael Rubinstein, Huiwen Chang, Katherine L. Bouman, William T. Freeman

Towards Universal Image Embeddings: A Large-Scale Dataset and Challenge for Generic Image Representations
Nikolaos-Antonios Ypsilantis, Kaifeng Chen, Bingyi Cao, Mario Lipovsky, Pelin Dogan-Schonberger, Grzegorz Makosa, Boris Bluntschli, Mojtaba Seyedhosseini, Ondrej Chum, André Araujo

U-RED: Unsupervised 3D Shape Retrieval and Deformation for Partial Point Clouds
Yan Di, Chenyangguang Zhang, Ruida Zhang, Fabian Manhardt, Yongzhi Su, Jason Rambach, Didier Stricker, Xiangyang Ji, Federico Tombari

AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Control
Ruixiang Jiang, Can Wang, Jingbo Zhang, Menglei Chai, Mingming He, Dongdong Chen, Jing Liao

Learning Versatile 3D Shape Generation with Improved AR Models
Simian Luo, Xuelin Qian, Yanwei Fu, Yinda Zhang, Ying Tai, Zhenyu Zhang, Chengjie Wang, Xiangyang Xue

Novel-view Synthesis and Pose Estimation for Hand-Object Interaction from Sparse Views
Wentian Qu, Zhaopeng Cui, Yinda Zhang, Chenyu Meng, Cuixia Ma, Xiaoming Deng, Hongan Wang

PreSTU: Pre-Training for Scene-Text Understanding
Jihyung Kil*, Soravit Changpinyo, Xi Chen, Hexiang Hu, Sebastian Goodman, Wei-Lun Chao, Radu Soricut

Self-supervised Learning of Implicit Shape Representation with Dense Correspondence for Deformable Objects
Baowen Zhang, Jiahe Li, Xiaoming Deng, Yinda Zhang, Cuixia Ma, Hongan Wang

Self-regulating Prompts: Foundational Model Adaptation without Forgetting
Muhammad Uzair Khattak, Syed Talal Wasi, Muzammal Nasee, Salman Kha, Ming-Hsuan Yan, Fahad Shahbaz Khan

Spectral Graphormer: Spectral Graph-Based Transformer for Egocentric Two-Hand Reconstruction using Multi-View Color Images
Tze Ho Elden Tse*, Franziska Mueller, Zhengyang Shen, Danhang Tang, Thabo Beeler, Mingsong Dou, Yinda Zhang, Sasa Petrovic, Hyung Jin Chang, Jonathan Taylor, Bardia Doosti

Synthesizing Diverse Human Motions in 3D Indoor Scenes
Kaifeng Zhao, Yan Zhang, Shaofei Wang, Thabo Beeler, Siyu Tang

Tracking by 3D Model Estimation of Unknown Objects in Videos
Denys Rozumnyi, Jiri Matas, Marc Pollefeys, Vittorio Ferrari, Martin R. Oswald

UnLoc: A Unified Framework for Video Localization Tasks
Shen Yan, Xuehan Xiong, Arsha Nagrani, Anurag Arnab, Zhonghao Wang*, Weina Ge, David Ross, Cordelia Schmid

Verbs in Action: Improving Verb Understanding in Video-language Models
Liliane Momeni, Mathilde Caron, Arsha Nagrani, Andrew Zisserman, Cordelia Schmid

VLSlice: Interactive Vision-and-Language Slice Discovery
Eric Slyman, Minsuk Kahng, Stefan Lee

Yes, we CANN: Constrained Approximate Nearest Neighbors for Local Feature-Based Visual Localization
Dror Aiger, André Araujo, Simon Lynen

Audiovisual Masked Autoencoders
Mariana-Iuliana Georgescu*, Eduardo Fonseca, Radu Tudor Ionescu, Mario Lucic, Cordelia Schmid, Anurag Arnab

CLR: Channel-wise Lightweight Reprogramming for Continual Learning
Yunhao Ge, Yuecheng Li, Shuo Ni, Jiaping Zhao, Ming-Hsuan Yang, Laurent Itti

LU-NeRF: Scene and Pose Estimation by Synchronizing Local Unposed NeRFs
Zezhou Cheng*, Carlos Esteves, Varun Jampani, Abhishek Kar, Subhransu Maji, Ameesh Makadia

Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering
Dongting Hu, Zhenkai Zhang, Tingbo Hou, Tongliang Liu, Huan Fu, Mingming Gong

Nerfbusters: Removing Ghostly Artifacts from Casually Captured NeRFs
Frederik Warburg, Ethan Weber, Matthew Tancik, Aleksander Holynski, Angjoo Kanazawa

Segmenting Known Objects and Unseen Unknowns without Prior Knowledge
Stefano Gasperini, Alvaro Marcos-Ramiro, Michael Schmidt, Nassir Navab, Benjamin Busam, Federico Tombari

SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detection
Yichen Xie, Chenfeng Xu, Marie-Julie Rakotosaona, Patrick Rim, Federico Tombari, Kurt Keutzer, Masayoshi Tomizuka, Wei Zhan

SwiftFormer: Efficient Additive Attention for Transformer-Based Real-time Mobile Vision Applications
Abdelrahman Shaker, Muhammad Maa, Hanoona Rashee, Salman Kha, Ming-Hsuan Yan, Fahad Shahbaz Kha

Agile Modeling: From Concept to Classifier in Minutes
Otilia Stretcu, Edward Vendrow, Kenji Hata, Krishnamurthy Viswanathan, Vittorio Ferrari, Sasan Tavakkol, Wenlei Zhou, Aditya Avinash, Enming Luo, Neil Gordon Alldrin, MohammadHossein Bateni, Gabriel Berger, Andrew Bunner, Chun-Ta Lu, Javier A Rey, Giulia DeSalvo, Ranjay Krishna, Ariel Fuxman

CAD-Estate: Large-Scale CAD Model Annotation in RGB Videos
Kevis-Kokitsi Maninis, Stefan Popov, Matthias Niessner, Vittorio Ferrari

Counting Crowds in Bad Weather
Zhi-Kai Huang, Wei-Ting Chen, Yuan-Chun Chiang, Sy-Yen Kuo, Ming-Hsuan Yang

DreamPose: Fashion Video Synthesis with Stable Diffusion
Johanna Karras, Aleksander Holynski, Ting-Chun Wang, Ira Kemelmacher-Shlizerman

InfiniCity: Infinite-Scale City Synthesis
Chieh Hubert Lin, Hsin-Ying Lee, Willi Menapace, Menglei Chai, Aliaksandr Siarohin, Ming-Hsuan Yang, Sergey Tulyakov

SAMPLING: Scene-Adaptive Hierarchical Multiplane Images Representation for Novel View Synthesis from a Single Image
Xiaoyu Zhou, Zhiwei Lin, Xiaojun Shan, Yongtao Wang, Deqing Sun, Ming-Hsuan Yang


Learning with Noisy and Unlabeled Data for Large Models beyond Categorization
Sifei Liu, Hongxu Yin, Shalini De Mello, Pavlo Molchanov, Jose M. Alvarez, Jan Kautz, Xiaolong Wang, Anima Anandkumar, Ming-Hsuan Yang, Trevor Darrell
Speaker: Varun Jampani


LatinX in AI
Platinum Sponsor
Panelists: Daniel Castro Chin, Andre Araujo
Invited Speaker: Irfan Essa
Volunteers: Ming-Hsuan Yang, Liangzhe Yuan, Pedro Velez, Vincent Etter

Scene Graphs and Graph Representation Learning
Organizer: Federico Tombari

International Workshop on Analysis and Modeling of Faces and Gestures
Speaker: Todd Zickler

3D Vision and Modeling Challenges in eCommerce
Speaker: Leonidas Guibas

BigMAC: Big Model Adaptation for Computer Vision
Organizer: Mathilde Caron

Adversarial Robustness In the Real World (AROW)
Organizer: Yutong Bai

GeoNet: 1st Workshop on Robust Computer Vision across Geographies
Speaker: Sara Beery
Organizer: Tarun Kalluri

Quo Vadis, Computer Vision?
Speaker: Bill Freeman

To NeRF or not to NeRF: A View Synthesis Challenge for Human Heads
Speaker: Thabo Beeler
Organizer: Stefanos Zafeiriou

New Ideas in Vision Transformers
Speaker: Cordelia Schmid
Organizer: Ming-Hsuan Yang

Representation Learning with Very Limited Images: The Potential of Self, Synthetic and Formula Supervision
Speaker: Manel Baradad Jurjo

Resource Efficient Deep Learning for Computer Vision
Speaker: Prateek Jain
Organizer: Jiahui Yu, Rishabh Tiwari, Jai Gupta

Computer Vision Aided Architectural Design
Speaker: Noah Snavely

AV4D: Visual Learning of Sounds in Spaces
Organizer: David Harwath

Vision-and-Language Algorithmic Reasoning
Speaker: François Chollet

Neural Fields for Autonomous Driving and Robotics
Speaker: Jon Barron

International Challenge on Compositional and Multimodal Perception
Organizer: Ranjay Krishna

Open-Vocabulary 3D Scene Understanding (OpenSUN3D)
Speaker: Thomas Funkhouser
Organizer: Francis Engelmann, Johanna Wald, Federico Tombari, Leonidas Guibas

Frontiers of Monocular 3D Perception: Geometric Foundation Models
Speaker: Leonidas Guibas

PerDream: PERception, Decision Making and REAsoning Through Multimodal Foundational Modeling
Organizer: Daniel McDuff

Recovering 6D Object Pose
Speaker: Fabian Manhardt, Martin Sundermeyer
Organizer: Martin Sundermeyer

Women in Computer Vision (WiCV)
Panelist: Arsha Nagrani

Language for 3D Scenes
Organizer: Leonidas Guibas

AI for 3D Content Creation
Speaker: Kai-Hung Chang
Organizer: Leonidas Guibas

Computer Vision for Metaverse
Speaker: Jon Barron, Thomas Funkhouser

Towards the Next Generation of Computer Vision Datasets
Speaker: Tom Duerig

* Work done while at Google

Source: Google AI Blog

Google at Interspeech 2023

This week, the 24th Annual Conference of the International Speech Communication Association (INTERSPEECH 2023) is being held in Dublin, Ireland, representing one of the world’s most extensive conferences on research and technology of spoken language understanding and processing. Experts in speech-related research fields gather to take part in oral presentations and poster sessions and to build collaborations across the globe.

We are excited to be a Platinum Sponsor of INTERSPEECH 2023, where we will be showcasing more than 20 research publications and supporting a number of workshops and special sessions. We welcome in-person attendees to drop by the Google Research booth to meet our researchers and participate in Q&As and demonstrations of some of our latest speech technologies, which help to improve accessibility and provide convenience in communication for billions of users. In addition, online attendees are encouraged to visit our virtual booth in Topia where you can get up-to-date information on research and opportunities at Google. Visit the @GoogleAI Twitter account to find out about Google booth activities (e.g., demos and Q&A sessions). You can also learn more about the Google research being presented at INTERSPEECH 2023 below (Google affiliations in bold).

Board and Organizing Committee

ISCA Board, Technical Committee Chair: Bhuvana Ramabhadran

Area Chairs include:
    Analysis of Speech and Audio Signals: Richard Rose
    Speech Synthesis and Spoken Language Generation: Rob Clark
    Special Areas: Tara Sainath

Satellite events

VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC-23)
Organizers include: Arsha Nagrani

ISCA Speech Synthesis Workshop (SSW12)
Speakers include: Rob Clark

Keynote talk – ISCA Medalist

Survey Talk

Speech Compression in the AI Era
Speaker: Jan Skoglund

Special session papers

Cascaded Encoders for Fine-Tuning ASR Models on Overlapped Speech
Richard Rose, Oscar Chang, Olivier Siohan

TokenSplit: Using Discrete Speech Representations for Direct, Refined, and Transcript-Conditioned Speech Separation and Recognition
Hakan Erdogan, Scott Wisdom, Xuankai Chang*, Zalán Borsos, Marco Tagliasacchi, Neil Zeghidour, John R. Hershey


DeePMOS: Deep Posterior Mean-Opinion-Score of Speech
Xinyu Liang, Fredrik Cumlin, Christian Schüldt, Saikat Chatterjee

O-1: Self-Training with Oracle and 1-Best Hypothesis
Murali Karthick Baskar, Andrew Rosenberg, Bhuvana Ramabhadran, Kartik Audhkhasi

Re-investigating the Efficient Transfer Learning of Speech Foundation Model Using Feature Fusion Methods
Zhouyuan Huo, Khe Chai Sim, Dongseong Hwang, Tsendsuren Munkhdalai, Tara N. Sainath, Pedro Moreno

MOS vs. AB: Evaluating Text-to-Speech Systems Reliably Using Clustered Standard Errors
Joshua Camp, Tom Kenter, Lev Finkelstein, Rob Clark

LanSER: Language-Model Supported Speech Emotion Recognition
Taesik Gong, Josh Belanich, Krishna Somandepalli, Arsha Nagrani, Brian Eoff, Brendan Jou

Modular Domain Adaptation for Conformer-Based Streaming ASR
Qiujia Li, Bo Li, Dongseong Hwang, Tara N. Sainath, Pedro M. Mengibar

On Training a Neural Residual Acoustic Echo Suppressor for Improved ASR
Sankaran Panchapagesan, Turaj Zakizadeh Shabestary, Arun Narayanan

MD3: The Multi-dialect Dataset of Dialogues
Jacob Eisenstein, Vinodkumar Prabhakaran, Clara Rivera, Dorottya Demszky, Devyani Sharma

Dual-Mode NAM: Effective Top-K Context Injection for End-to-End ASR
Zelin Wu, Tsendsuren Munkhdalai, Pat Rondon, Golan Pundak, Khe Chai Sim, Christopher Li

Using Text Injection to Improve Recognition of Personal Identifiers in Speech
Yochai Blau, Rohan Agrawal, Lior Madmony, Gary Wang, Andrew Rosenberg, Zhehuai Chen, Zorik Gekhman, Genady Beryozkin, Parisa Haghani, Bhuvana Ramabhadran

How to Estimate Model Transferability of Pre-trained Speech Models?
Zih-Ching Chen, Chao-Han Huck Yang*, Bo Li, Yu Zhang, Nanxin Chen, Shuo-yiin Chang, Rohit Prabhavalkar, Hung-yi Lee, Tara N. Sainath

Improving Joint Speech-Text Representations Without Alignment
Cal Peyser, Zhong Meng, Ke Hu, Rohit Prabhavalkar, Andrew Rosenberg, Tara N. Sainath, Michael Picheny, Kyunghyun Cho

Text Injection for Capitalization and Turn-Taking Prediction in Speech Models
Shaan Bijwadia, Shuo-yiin Chang, Weiran Wang, Zhong Meng, Hao Zhang, Tara N. Sainath

Streaming Parrotron for On-Device Speech-to-Speech Conversion
Oleg Rybakov, Fadi Biadsy, Xia Zhang, Liyang Jiang, Phoenix Meadowlark, Shivani Agrawal

Semantic Segmentation with Bidirectional Language Models Improves Long-Form ASR
W. Ronny Huang, Hao Zhang, Shankar Kumar, Shuo-yiin Chang, Tara N. Sainath

Universal Automatic Phonetic Transcription into the International Phonetic Alphabet
Chihiro Taguchi, Yusuke Sakai, Parisa Haghani, David Chiang

Mixture-of-Expert Conformer for Streaming Multilingual ASR
Ke Hu, Bo Li, Tara N. Sainath, Yu Zhang, Francoise Beaufays

Real Time Spectrogram Inversion on Mobile Phone
Oleg Rybakov, Marco Tagliasacchi, Yunpeng Li, Liyang Jiang, Xia Zhang, Fadi Biadsy

2-Bit Conformer Quantization for Automatic Speech Recognition
Oleg Rybakov, Phoenix Meadowlark, Shaojin Ding, David Qiu, Jian Li, David Rim, Yanzhang He

LibriTTS-R: A Restored Multi-speaker Text-to-Speech Corpus
Yuma Koizumi, Heiga Zen, Shigeki Karita, Yifan Ding, Kohei Yatabe, Nobuyuki Morioka, Michiel Bacchiani, Yu Zhang, Wei Han, Ankur Bapna

PronScribe: Highly Accurate Multimodal Phonemic Transcription from Speech and Text
Yang Yu, Matthew Perez*, Ankur Bapna, Fadi Haik, Siamak Tazari, Yu Zhang

Label Aware Speech Representation Learning for Language Identification
Shikhar Vashishth, Shikhar Bharadwaj, Sriram Ganapathy, Ankur Bapna, Min Ma, Wei Han, Vera Axelrod, Partha Talukdar

* Work done while at Google

Source: Google AI Blog

Google at ICML 2023

Groups across Google actively pursue research in the field of machine learning (ML), ranging from theory and application. We build ML systems to solve deep scientific and engineering challenges in areas of language, music, visual processing, algorithm development, and more. We aim to build a more collaborative ecosystem with the broader ML research community through open-sourcing tools and datasets, publishing our work, and actively participating in conferences.

Google is proud to be a Diamond Sponsor of the 40th International Conference on Machine Learning (ICML 2023), a premier annual conference, which is being held this week in Honolulu, Hawaii. As a leader in ML research, Google has a strong presence at this year’s conference with over 120 accepted papers and active involvement in a number of workshops and tutorials. Google is also proud to be a Platinum Sponsor for both the LatinX in AI and Women in Machine Learning workshops. We look forward to sharing some of our extensive ML research and expanding our partnership with the broader ML research community.

Registered for ICML 2023? We hope you’ll visit the Google booth to learn more about the exciting work, creativity, and fun that goes into solving a portion of the field’s most interesting challenges. Visit the @GoogleAI Twitter account to find out about Google booth activities (e.g., demos and Q&A sessions). See Google DeepMind’s blog to learn about their technical participation at ICML 2023.

Take a look below to learn more about the Google research being presented at ICML 2023 (Google affiliations in bold).

Board and Organizing Committee

Board Members include: Corinna Cortes, Hugo Larochelle
Tutorial Chairs include: Hanie Sedghi

Google Research booth activities

Presenters: Bryan Perozzi, Anton Tsitsulin, Brandon Mayer
Title: Unsupervised Graph Embedding @ Google (paper, EXPO workshop)
Tuesday, July 25th at 10:30 AM HST

Presenters: Zheng Xu
Title: Federated Learning of Gboard Language Models with Differential Privacy (paper 1, paper 2, blog post)
Tuesday, July 25th at 3:30 PM HST

Presenters: Thomas Kipf
Title: Self-supervised scene understanding (paper 1, paper 2)
Wednesday, July 26th at 10:30 AM HST

Presenters: Johannes von Oswald, Max Vladymyrov
Title: Transformers learn in-context by gradient descent (paper)
Wednesday, July 26th at 3:30 PM HST

Accepted papers

Scaling Vision Transformers to 22 Billion Parameters (see blog post)
Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin F. Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Patrick Collier, Alexey Gritsenko, Vighnesh Birodkar, Cristina Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetić, Dustin Tran, Thomas Kipf, Mario Lučić, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby

Fast Inference from Transformers via Speculative Decoding
Yaniv Leviathan, Matan Kalman, Yossi Matias

Best of Both Worlds Policy Optimization
Christoph Dann, Chen-Yu Wei, Julian Zimmert

Inflow, Outflow, and Reciprocity in Machine Learning
Mukund Sundararajan, Walid Krichene

Transformers Learn In-Context by Gradient Descent
Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, João Sacramento, Alexander Mordvintsev, Andrey Zhmoginov, Max Vladymyrov

Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models
Luke Vilnis, Yury Zemlyanskiy, Patrick Murray*, Alexandre Passos*, Sumit Sanghai

Differentially Private Hierarchical Clustering with Provable Approximation Guarantees (see blog post)
Jacob Imola*, Alessandro Epasto, Mohammad Mahdian, Vincent Cohen-Addad, Vahab Mirrokni

Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning
Christopher A. Choquette-Choo, H. Brendan McMahan, Keith Rush, Abhradeep Thakurta

Random Classification Noise Does Not Defeat All Convex Potential Boosters Irrespective of Model Choice
Yishay Mansour, Richard Nock, Robert Williamson

Simplex Random Features
Isaac Reid, Krzysztof Choromanski, Valerii Likhosherstov, Adrian Weller

Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding
Kenton Lee, Mandar Joshi, Iulia Turc, Hexiang Hu, Fangyu Liu, Julian Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, Kristina Toutanova

Mu2SLAM: Multitask, Multilingual Speech and Language Models
Yong Cheng, Yu Zhang, Melvin Johnson, Wolfgang Macherey, Ankur Bapna

Robust Budget Pacing with a Single Sample
Santiago Balseiro, Rachitesh Kumar*, Vahab Mirrokni, Balasubramanian Sivan, Di Wang

A Statistical Perspective on Retrieval-Based Models
Soumya Basu, Ankit Singh Rawat, Manzil Zaheer

Approximately Optimal Core Shapes for Tensor Decompositions
Mehrdad Ghadiri, Matthew Fahrbach, Gang Fu, Vahab Mirrokni

Efficient List-Decodable Regression Using Batches
Abhimanyu Das, Ayush Jain*, Weihao Kong, Rajat Sen

Efficient Training of Language Models Using Few-Shot Learning
Sashank J. Reddi, Sobhan Miryoosefi, Stefani Karp, Shankar Krishnan, Satyen Kale, Seungyeon Kim, Sanjiv Kumar

Fully Dynamic Submodular Maximization Over Matroids
Paul Duetting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard, Morteza Zadimoghaddam

GFlowNet-EM for Learning Compositional Latent Variable Models
Edward J Hu, Nikolay Malkin, Moksh Jain, Katie Everett, Alexandros Graikos, Yoshua Bengio

Improved Online Learning Algorithms for CTR Prediction in Ad Auctions
Zhe Feng, Christopher Liaw, Zixin Zhou

Large Language Models Struggle to Learn Long-Tail Knowledge
Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, Colin Raffel

Multi-channel Autobidding with Budget and ROI Constraints
Yuan Deng, Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni

Multi-layer Neural Networks as Trainable Ladders of Hilbert Spaces
Zhengdao Chen

On User-Level Private Convex Optimization
Badih Ghazi, Pritish Kamath, Ravi Kumar, Raghu Meka, Pasin Manurangsi, Chiyuan Zhang

PAC Generalization via Invariant Representations
Advait U Parulekar, Karthikeyan Shanmugam, Sanjay Shakkottai

Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Menard, Mohammad Gheshlaghi Azar, Remi Munos, Olivier Pietquin, Matthieu Geist,Csaba Szepesvari, Wataru Kumagai, Yutaka Matsuo

Speeding Up Bellman Ford via Minimum Violation Permutations
Silvio Lattanzi, Ola Svensson, Sergei Vassilvitskii

Statistical Indistinguishability of Learning Algorithms
Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas

Test-Time Adaptation with Slot-Centric Models
Mihir Prabhudesai, Anirudh Goyal, Sujoy Paul, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Gaurav Aggarwal, Thomas Kipf, Deepak Pathak, Katerina Fragkiadaki>

Algorithms for Bounding Contribution for Histogram Estimation Under User-Level Privacy
Yuhan Liu*, Ananda Theertha Suresh, Wennan Zhu, Peter Kairouz, Marco Gruteser

Bandit Online Linear Optimization with Hints and Queries
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit

CLUTR: Curriculum Learning via Unsupervised Task Representation Learning
Abdus Salam Azad, Izzeddin Gur, Jasper Emhoff, Nathaniel Alexis, Aleksandra Faust, Pieter Abbeel, Ion Stoica

CSP: Self-Supervised Contrastive Spatial Pre-training for Geospatial-Visual Representations
Gengchen Mai, Ni Lao, Yutong He, Jiaming Song, Stefano Ermon

Ewald-Based Long-Range Message Passing for Molecular Graphs
Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Günnemann

Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization
Ameya Velingker, Maximilian Vötsch, David Woodruff, Samson Zhou

Federated Linear Contextual Bandits with User-Level Differential Privacy
Ruiquan Huang, Huanyu Zhang, Luca Melis, Milan Shen, Meisam Hejazinia, Jing Yang

Investigating the Role of Model-Based Learning in Exploration and Transfer
Jacob C Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Theophane Weber, Jessica B Hamrick

Label Differential Privacy and Private Training Data Release
Robert Busa-Fekete, Andres Munoz, Umar Syed, Sergei Vassilvitskii

Lifelong Language Pretraining with Distribution-Specialized Experts
Wuyang Chen*, Yanqi Zhou, Nan Du, Yanping Huang, James Laudon, Zhifeng Chen, Claire Cui

Multi-User Reinforcement Learning with Low Rank Rewards
Dheeraj Mysore Nagaraj, Suhas S Kowshik, Naman Agarwal, Praneeth Netrapalli, Prateek Jain

Multi-View Masked World Models for Visual Robotic Manipulation
Younggyo Seo, Junsu Kim, Stephen James, Kimin Lee, Jinwoo Shin, Pieter Abbeel

PaLM-E: An Embodied Multimodal Language Model (see blog post)
Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter,Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, Pete Florence

Private Federated Learning with Autotuned Compression
Enayat Ullah*, Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh

Refined Regret for Adversarial MDPs with Linear Function Approximation
Yan Dai, Haipeng Luo, Chen-Yu Wei, Julian Zimmert

Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory
Justin Cui, Ruoche Wan, Si Si, Cho-Jui Hsieh

SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance
Amit Attia, Tomer Koren

The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation
Mark Rowland, Yunhao Tang, Clare Lyle, Rémi Munos, Marc G. Bellemare, Will Dabney

Unveiling The Mask of Position-Information Pattern Through the Mist of Image Features
Chieh Hubert Lin, Hung-Yu Tseng, Hsin-Ying Lee, Maneesh Kumar Singh, Ming-Hsuan Yang

User-Level Private Stochastic Convex Optimization with Optimal Rates
Raef Bassily, Ziteng Sun

A Simple Zero-Shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models
James Urquhart Allingham*, Jie Ren, Michael W Dusenberry, Xiuye Gu, Yin Cui, Dustin Tran, Jeremiah Zhe Liu, Balaji Lakshminarayanan

Can Large Language Models Reason About Program Invariants?
Kexin Pei, David Bieber, Kensen Shi, Charles Sutton, Pengcheng Yin

Concurrent Shuffle Differential Privacy Under Continual Observation
Jay Tenenbaum, Haim Kaplan, Yishay Mansour, Uri Stemmer

Constant Matters: Fine-Grained Error Bound on Differentially Private Continual Observation
Hendrik Fichtenberger, Monika Henzinger, Jalaj Upadhyay

Cross-Entropy Loss Functions: Theoretical Analysis and Applications
Anqi Mao, Mehryar Mohri, Yutao Zhong

Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation
Orin Levy, Alon Cohen, Asaf Cassel, Yishay Mansour

Fairness in Streaming Submodular Maximization Over a Matroid Constraint
Marwa El Halabi, Federico Fusco, Ashkan Norouzi-Fard, Jakab Tardos, Jakub Tarnawski

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning (see blog post)
Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V Le, Barret Zoph, Jason Wei, Adam Roberts

Graph Reinforcement Learning for Network Control via Bi-level Optimization
Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira

Learning-Augmented Private Algorithms for Multiple Quantile Release
Mikhail Khodak*, Kareem Amin, Travis Dick, Sergei Vassilvitskii

LegendreTron: Uprising Proper Multiclass Loss Learning
Kevin H Lam, Christian Walder, Spiridon Penev, Richard Nock

Measuring the Impact of Programming Language Distribution
Gabriel Orlanski*, Kefan Xiao, Xavier Garcia, Jeffrey Hui, Joshua Howland, Jonathan Malmaud, Jacob Austin, Rishabh Singh, Michele Catasta*

Multi-task Differential Privacy Under Distribution Skew
Walid Krichene, Prateek Jain, Shuang Song, Mukund Sundararajan, Abhradeep Thakurta, Li Zhang

Muse: Text-to-Image Generation via Masked Generative Transformers
Huiwen Chang, Han Zhang, Jarred Barber, AJ Maschinot, José Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Murphy, William T. Freeman, Michael Rubinstein, Yuanzhen Li, Dilip Krishnan

On the Convergence of Federated Averaging with Cyclic Client Participation
Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang

Optimal Stochastic Non-smooth Non-convex Optimization Through Online-to-Non-convex Conversion
Ashok Cutkosky, Harsh Mehta, Francesco Orabona

Out-of-Domain Robustness via Targeted Augmentations
Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang

Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models
Jamil Arbas, Hassan Ashtiani, Christopher Liaw

Pre-computed Memory or On-the-Fly Encoding? A Hybrid Approach to Retrieval Augmentation Makes the Most of Your Compute
Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen

Scalable Adaptive Computation for Iterative Generation
Allan Jabri*, David J. Fleet, Ting Chen

Scaling Spherical CNNs
Carlos Esteves, Jean-Jacques Slotine, Ameesh Makadia

STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition
Yucheng Lu, Shivani Agrawal, Suvinay Subramanian, Oleg Rybakov, Christopher De Sa, Amir Yazdanbakhsh

Stratified Adversarial Robustness with Rejection
Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha

When Does Privileged information Explain Away Label Noise?
Guillermo Ortiz-Jimenez*, Mark Collier, Anant Nawalgaria, Alexander D'Amour, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou

Adaptive Computation with Elastic Input Sequence
Fuzhao Xue*, Valerii Likhosherstov, Anurag Arnab, Neil Houlsby, Mostafa Dehghani, Yang You

Can Neural Network Memorization Be Localized?
Pratyush Maini, Michael C. Mozer, Hanie Sedghi, Zachary C. Lipton, J. Zico Kolter, Chiyuan Zhang

Controllability-Aware Unsupervised Skill Discovery
Seohong Park, Kimin Lee, Youngwoon Lee, Pieter Abbeel

Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network
Yadi Cao, Menglei Chai, Minchen Li, Chenfanfu Jiang

Federated Heavy Hitter Recovery Under Linear Sketching
Adria Gascon, Peter Kairouz, Ziteng Sun, Ananda Theertha Suresh

Graph Generative Model for Benchmarking Graph Neural Networks
Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov

H-Consistency Bounds for Pairwise Misranking Loss Surrogates
Anqi Mao, Mehryar Mohri, Yutao Zhong

Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation
Uri Sherman, Tomer Koren, Yishay Mansour

Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames
Ondrej Biza*, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Thomas Kipf

Multi-task Off-Policy Learning from Bandit Feedback
Joey Hong, Branislav Kveton, Manzil Zaheer, Sumeet Katariya, Mohammad Ghavamzadeh

Optimal No-Regret Learning for One-Sided Lipschitz Functions
Paul Duetting, Guru Guruganesh, Jon Schneider, Joshua Ruizhi Wang

Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games
Batuhan Yardim, Semih Cayci, Matthieu Geist, Niao He

Regret Minimization and Convergence to Equilibria in General-Sum Markov Games
Liad Erez, Tal Lancewicki, Uri Sherman, Tomer Koren, Yishay Mansour

Reinforcement Learning Can Be More Efficient with Multiple Rewards
Christoph Dann, Yishay Mansour, Mehryar Mohri

Reinforcement Learning with History-Dependent Dynamic Contexts
Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutlier

User-Defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems
Marc Anton Finzi*, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, Leonardo Zepeda-Nunez

Discrete Key-Value Bottleneck
Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf

DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm
Lisang Ding, Kexin Jin, Bicheng Ying, Kun Yuan, Wotao Yin

Exphormer: Sparse Transformers for Graphs
Hamed Shirzad, Ameya Velingker, Balaji Venkatachalam, Danica J. Sutherland, Ali Kemal Sinop

Fast, Differentiable and Sparse Top-k: A Convex Analysis Perspective
Michael Eli Sander*, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel

Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation
Aditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe

In Search for a Generalizable Method for Source Free Domain Adaptation
Malik Boudiaf*, Tom Denton, Bart van Merrienboer, Vincent Dumoulin, Eleni Triantafillou

Learning Rate Schedules in the Presence of Distribution Shift
Matthew Fahrbach, Adel Javanmard, Vahab Mirrokni, Pratik Worah

Not All Semantics Are Created Equal: Contrastive Self-Supervised Learning with Automatic Temperature Individualization
Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang

On the Relationship Between Explanation and Prediction: A Causal View
Amir-Hossein Karimi*, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, Been Kim

On the Role of Attention in Prompt-Tuning
Samet Oymak, Ankit Singh Rawat, Mahdi Soltanolkotabi, Christos Thrampoulidis

PLay: Parametrically Conditioned Layout Generation Using Latent Diffusion
Chin-Yi Cheng, Forrest Huang, Gang Li, Yang Li

The Power of Learned Locally Linear Models for Nonlinear Policy Optimization
Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek, Nikolai Matni, Stephen Tu

Relevant Walk Search for Explaining Graph Neural Networks
Ping Xiong, Thomas Schnake, Michael Gastegger, Grégoire Montavon, Klaus Robert Muller,Shinichi Nakajima

Repository-Level Prompt Generation for Large Language Models of Code
Disha Shrivastava, Hugo Larochelle, Daniel Tarlow

Robust and Private Stochastic Linear Bandits
Vasileios Charisopoulos*, Hossein Esfandiari, Vahab Mirrokni

Simple Diffusion: End-to-End Diffusion for High Resolution Images
Emiel Hoogeboom, Jonathan Heek, Tim Salimans

Tied-Augment: Controlling Representation Similarity Improves Data Augmentation
Emirhan Kurtulus, Zichao Li, Yann Dauphin, Ekin D. Cubuk

Why Is Public Pre-Training Necessary for Private Model Training?
Arun Ganesh, Mahdi Haghifam*, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Guha Thakurta, Lun Wang

A Connection Between One-Step RL and Critic Regularization in Reinforcement Learning
Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov

Beyond Uniform Lipschitz Condition in Differentially Private Optimization
Rudrajit Das*, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi

Efficient Graph Field Integrators Meet Point Clouds
Krzysztof Choromanski, Arijit Sehanobish, Han Lin, Yunfan Zhao, Eli Berger, Tetiana Parshakova, Alvin Pan, David Watkins, Tianyi Zhang, Valerii Likhosherstov, Somnath Basu Roy Chowdhury, Avinava Dubey, Deepali Jain, Tamas Sarlos, Snigdha Chaturvedi, Adrian Weller

Fast as CHITA: Neural Network Pruning with Combinatorial Optimization
Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder

Jump-Start Reinforcement Learning (see blog post)
Ikechukwu Uchendu*, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman

Learning in POMDPs is Sample-Efficient with Hindsight Observability
Jonathan Lee, Alekh Agarwal, Christoph Dann, Tong Zhang

Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single
Paul Vicol

Masked Trajectory Models for Prediction, Representation, and Control
Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran

Overcoming Simplicity Bias in Deep Networks Using a Feature Sieve
Rishabh Tiwari, Pradeep Shenoy

Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions
Boxiang Lyu, Zhe Feng, Zachary Robertson, Sanmi Koyejo

Predictive Flows for Faster Ford-Fulkerson
Sami Davies, Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang

Scaling Laws for Multilingual Neural Machine Translation
Patrick Fernandes, Behrooz Ghorbani, Xavier Garcia, Markus Freitag, Orhan Firat

Sequential Monte Carlo Learning for Time Series Structure Discovery
Feras Saad, Brian Patton, Matthew Douglas Hoffman, Rif A. Saurous, Vikash Mansinghka

Stochastic Gradient Succeeds for Bandits
Jincheng Mei, Zixin Zhong, Bo Dai, Alekh Agarwal, Csaba Szepesvari, Dale Schuurmans

Subset-Based Instance Optimality in Private Estimation
Travis Dick, Alex Kulesza, Ziteng Sun, Ananda Theertha Suresh

The Unreasonable Effectiveness of Few-Shot Learning for Machine Translation
Xavier Garcia, Yamini Bansal, Colin Cherry, George Foster, Maxim Krikun, Melvin Johnson, Orhan Firat


Self-Supervised Learning in Vision: from Research Advances to Best Practices
Xinlei Chen, Ishan Misra, Randall Balestriero, Mathilde Caron, Christoph Feichtenhofer, Mark Ibrahim

How to DP-fy ML: A Practical Tutorial to Machine Learning with Differential Privacy (see blog post)
Sergei Vassilvitskii, Natalia Ponomareva, Zheng Xu

Recent Advances in the Generalization Theory of Neural Networks
Tengyu Ma, Alex Damian

EXPO Day workshops

Graph Neural Networks in Tensorflow: A Practical Guide
Workshop Organizers include: Bryan Perozzi, Anton Tsitsulin, Brandon Mayer, Jonathan Halcrow

Google sponsored affinity workshops

LatinX in AI (LAXAI)
Platinum Sponsor
Keynote Speaker: Monica Ribero
Panelist: Yao Qin

Women in Machine Learning (WiML)
Platinum Sponsor
Panelists: Yao Qin


Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities
Organizer: Peter Kairouz, Zheng Xu
Speaker: Brendan McMahan

Interpretable Machine Learning in Healthcare (IMLH)
Organizer: Ramin Zabih

Knowledge and Logical Reasoning in the Era of Data-Driven Learning
Organizer: Beliz Günel

The Many Facets of Preference-Based Learning (MFPL)
Organizer: Robert Busa-Fekete, Mohammad Ghavamzadeh

The Synergy of Scientific and Machine Learning Modelling (SynS & ML)
Speaker: Sercan Arik

Theory of Mind in Communicating Agents
Organizer: Pei Zhou

Artificial Intelligence & Human Computer Interaction
Organizer: Yang Li, Forrest Huang

Data-Centric Machine Learning Research (DMLR)
Organizer: Alicia Parrish, Najoung Kim
Speaker: Peter Mattson

Neural Compression: from Information Theory to Applications
Speaker: Johannes Ballé
Panelist: George Toderici

Neural Conversational AI Workshop - What’s Left to TEACH (Trustworthy, Enhanced, Adaptable, Capable and Human-centric) Chatbots?
Organizer: Ahmad Beirami

Spurious Correlations, Invariance and Stability (SCIS)
Organizer: Amir Feder

* Work done while at Google

Source: Google AI Blog

Google at ACL 2023

This week, the 61st annual meeting of the Association for Computational Linguistics (ACL), a premier conference covering a broad spectrum of research areas that are concerned with computational approaches to natural language, is taking place online.

As a leader in natural language processing and understanding, and a Diamond Level sponsor of ACL 2023, Google will showcase the latest research in the field with over 50 publications, and active involvement in a variety of workshops and tutorials.

If you’re registered for ACL 2023, we hope that you’ll visit the Google booth to learn more about the projects at Google that go into solving interesting problems for billions of people. You can also learn more about Google's participation below (Google affiliations in bold).

Board and Organizing Committee

Area chairs include: Dan Garrette
Workshop chairs include: Annie Louis
Publication chairs include: Lei Shu
Program Committee includes: Vinodkumar Prabhakaran, Najoung Kim, Markus Freitag

Spotlight papers

NusaCrowd: Open Source Initiative for Indonesian NLP Resources
Samuel Cahyawijaya, Holy Lovenia, Alham Fikri Aji, Genta Winata, Bryan Wilie, Fajri Koto, Rahmad Mahendra, Christian Wibisono, Ade Romadhony, Karissa Vincentio, Jennifer Santoso, David Moeljadi, Cahya Wirawan, Frederikus Hudi, Muhammad Satrio Wicaksono, Ivan Parmonangan, Ika Alfina, Ilham Firdausi Putra, Samsul Rahmadani, Yulianti Oenang, Ali Septiandri, James Jaya, Kaustubh Dhole, Arie Suryani, Rifki Afina Putri, Dan Su, Keith Stevens, Made Nindyatama Nityasya, Muhammad Adilazuarda, Ryan Hadiwijaya, Ryandito Diandaru, Tiezheng Yu, Vito Ghifari, Wenliang Dai, Yan Xu, Dyah Damapuspita, Haryo Wibowo, Cuk Tho, Ichwanul Karo Karo, Tirana Fatyanosa, Ziwei Ji, Graham Neubig, Timothy Baldwin, Sebastian Ruder, Pascale Fung, Herry Sujaini, Sakriani Sakti, Ayu Purwarianti

Optimizing Test-Time Query Representations for Dense Retrieval
Mujeen Sung, Jungsoo Park, Jaewoo Kang, Danqi Chen, Jinhyuk Lee

PropSegmEnt: A Large-Scale Corpus for Proposition-Level Segmentation and Entailment Recognition
Sihao Chen*, Senaka Buthpitiya, Alex Fabrikant, Dan Roth, Tal Schuster

Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
Cheng-Yu Hsieh*, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alex Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister

Large Language Models with Controllable Working Memory
Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix Yu, Sanjiv Kumar

OpineSum: Entailment-Based Self-Training for Abstractive Opinion Summarization
Annie Louis, Joshua Maynez

RISE: Leveraging Retrieval Techniques for Summarization Evaluation
David Uthus, Jianmo Ni

Follow the Leader(board) with Confidence: Estimating p-Values from a Single Test Set with Item and Response Variance
Shira Wein*, Christopher Homan, Lora Aroyo, Chris Welty

SamToNe: Improving Contrastive Loss for Dual Encoder Retrieval Models with Same Tower Negatives
Fedor Moiseev, Gustavo Hernandez Abrego, Peter Dornbach, Imed Zitouni, Enrique Alfonseca, Zhe Dong


Searching for Needles in a Haystack: On the Role of Incidental Bilingualism in PaLM's Translation Capability
Eleftheria Briakou, Colin Cherry, George Foster

Prompting PaLM for Translation: Assessing Strategies and Performance
David Vilar, Markus Freitag, Colin Cherry, Jiaming Luo, Viresh Ratnakar, George Foster

Query Refinement Prompts for Closed-Book Long-Form QA
Reinald Kim Amplayo, Kellie Webster, Michael Collins, Dipanjan Das, Shashi Narayan

To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering
Dheeru Dua*, Emma Strubell, Sameer Singh, Pat Verga

FRMT: A Benchmark for Few-Shot Region-Aware Machine Translation (see blog post)
Parker Riley, Timothy Dozat, Jan A. Botha, Xavier Garcia, Dan Garrette, Jason Riesa, Orhan Firat, Noah Constant

Conditional Generation with a Question-Answering Blueprint
Shashi Narayan, Joshua Maynez, Reinald Kim Amplayo, Kuzman Ganchev, Annie Louis, Fantine Huot, Anders Sandholm, Dipanjan Das, Mirella Lapata

Coreference Resolution Through a Seq2Seq Transition-Based System
Bernd Bohnet, Chris Alberti, Michael Collins

Cross-Lingual Transfer with Language-Specific Subnetworks for Low-Resource Dependency Parsing
Rochelle Choenni, Dan Garrette, Ekaterina Shutova

DAMP: Doubly Aligned Multilingual Parser for Task-Oriented Dialogue
William Held*, Christopher Hidey, Fei Liu, Eric Zhu, Rahul Goel, Diyi Yang, Rushin Shah

RARR: Researching and Revising What Language Models Say, Using Language Models
Luyu Gao*, Zhuyun Dai, Panupong Pasupat, Anthony Chen*, Arun Tejasvi Chaganty, Yicheng Fan, Vincent Y. Zhao, Ni Lao, Hongrae Lee, Da-Cheng Juan, Kelvin Guu

Benchmarking Large Language Model Capabilities for Conditional Generation
Joshua Maynez, Priyanka Agrawal, Sebastian Gehrmann

Crosslingual Generalization Through Multitask Fine-Tuning
Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts, Stella Biderman, Teven Le Scao, M. Saiful Bari, Sheng Shen, Zheng Xin Yong, Hailey Schoelkopf, Xiangru Tang, Dragomir Radev, Alham Fikri Aji, Khalid Almubarak, Samuel Albanie, Zaid Alyafeai, Albert Webson, Edward Raff, Colin Raffel

DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering
Ella Neeman, Roee Aharoni, Or Honovich, Leshem Choshen, Idan Szpektor, Omri Abend

Resolving Indirect Referring Expressions for Entity Selection
Mohammad Javad Hosseini, Filip Radlinski, Silvia Pareti, Annie Louis

SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models
Akshita Jha*, Aida Mostafazadeh Davani, Chandan K Reddy, Shachi Dave, Vinodkumar Prabhakaran, Sunipa Dev

The Tail Wagging the Dog: Dataset Construction Biases of Social Bias Benchmarks
Nikil Selvam, Sunipa Dev, Daniel Khashabi, Tushar Khot, Kai-Wei Chang

Character-Aware Models Improve Visual Text Rendering
Rosanne Liu, Dan Garrette, Chitwan Saharia, William Chan, Adam Roberts, Sharan Narang, Irina Blok, RJ Mical, Mohammad Norouzi, Noah Constant

Cold-Start Data Selection for Better Few-Shot Language Model Fine-Tuning: A Prompt-Based Uncertainty Propagation Approach
Yue Yu, Rongzhi Zhang, Ran Xu, Jieyu Zhang, Jiaming Shen, Chao Zhang

Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment
Roni Rabin, Alexandre Djerbetian, Roee Engelberg, Lidan Hackmon, Gal Elidan, Reut Tsarfaty, Amir Globerson

FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction
Chen-Yu Lee, Chun-Liang Li, Hao Zhang, Timothy Dozat, Vincent Perot, Guolong Su, Xiang Zhang, Kihyuk Sohn, Nikolay Glushinev, Renshen Wang, Joshua Ainslie, Shangbang Long, Siyang Qin, Yasuhisa Fujii, Nan Hua, Tomas Pfister

Dialect-Robust Evaluation of Generated Text
Jiao Sun*, Thibault Sellam, Elizabeth Clark, Tu Vu*, Timothy Dozat, Dan Garrette, Aditya Siddhant, Jacob Eisenstein, Sebastian Gehrmann

MISGENDERED: Limits of Large Language Models in Understanding Pronouns
Tamanna Hossain, Sunipa Dev, Sameer Singh

LAMBADA: Backward Chaining for Automated Reasoning in Natural Language
Mehran Kazemi, Najoung Kim, Deepti Bhatia, Xin Xu, Deepak Ramachandran

LAIT: Efficient Multi-Segment Encoding in Transformers with Layer-Adjustable Interaction
Jeremiah Milbauer*, Annie Louis, Mohammad Javad Hosseini, Alex Fabrikant, Donald Metzler, Tal Schuster

Modular Visual Question Answering via Code Generation (see blog post)
Sanjay Subramanian, Medhini Narasimhan, Kushal Khangaonkar, Kevin Yang, Arsha Nagrani, Cordelia Schmid, Andy Zeng, Trevor Darrell, Dan Klein

Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters
Boshi Wang, Sewon Min, Xiang Deng, Jiaming Shen, You Wu, Luke Zettlemoyer and Huan Sun

Better Zero-Shot Reasoning with Self-Adaptive Prompting
Xingchen Wan*, Ruoxi Sun, Hanjun Dai, Sercan Ö. Arik, Tomas Pfister

Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback
Paul Roit, Johan Ferret, Lior Shani, Roee Aharoni, Geoffrey Cideron, Robert Dadashi, Matthieu Geist, Sertan Girgin, Léonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor

Natural Language to Code Generation in Interactive Data Science Notebooks
Pengcheng Yin, Wen-Ding Li, Kefan Xiao, Abhishek Rao, Yeming Wen, Kensen Shi, Joshua Howland, Paige Bailey, Michele Catasta, Henryk Michalewski, Oleksandr Polozov, Charles Sutton

Teaching Small Language Models to Reason
Lucie Charlotte Magister*, Jonathan Mallinson, Jakub Adamek, Eric Malmi, Aliaksei Severyn

Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic
Connor Pryor*, Quan Yuan, Jeremiah Liu, Mehran Kazemi, Deepak Ramachandran, Tania Bedrax-Weiss, Lise Getoor

A Needle in a Haystack: An Analysis of High-Agreement Workers on MTurk for Summarization
Lining Zhang, Simon Mille, Yufang Hou, Daniel Deutsch, Elizabeth Clark, Yixin Liu, Saad Mahamood, Sebastian Gehrmann, Miruna Clinciu, Khyathi Raghavi Chandu and João Sedoc

Industry Track papers

Federated Learning of Gboard Language Models with Differential Privacy
Zheng Xu, Yanxiang Zhang, Galen Andrew, Christopher Choquette, Peter Kairouz, Brendan McMahan, Jesse Rosenstock, Yuanbo Zhang

KAFA: Rethinking Image Ad Understanding with Knowledge-Augmented Feature Adaptation of Vision-Language Models
Zhiwei Jia*, Pradyumna Narayana, Arjun Akula, Garima Pruthi, Hao Su, Sugato Basu, Varun Jampani

ACL Findings papers

Multilingual Summarization with Factual Consistency Evaluation
Roee Aharoni, Shashi Narayan, Joshua Maynez, Jonathan Herzig, Elizabeth Clark, Mirella Lapata

Parameter-Efficient Fine-Tuning for Robust Continual Multilingual Learning
Kartikeya Badola, Shachi Dave, Partha Talukdar

FiDO: Fusion-in-Decoder Optimized for Stronger Performance and Faster Inference
Michiel de Jong*, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William Cohen

A Simple, Yet Effective Approach to Finding Biases in Code Generation
Spyridon Mouselinos, Mateusz Malinowski, Henryk Michalewski

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
Mirac Suzgun, Nathan Scales, Nathanael Scharli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc Le, Ed Chi, Denny Zhou, Jason Wei

QueryForm: A Simple Zero-Shot Form Entity Query Framework
Zifeng Wang*, Zizhao Zhang, Jacob Devlin, Chen-Yu Lee, Guolong Su, Hao Zhang, Jennifer Dy, Vincent Perot, Tomas Pfister

ReGen: Zero-Shot Text Classification via Training Data Generation with Progressive Dense Retrieval
Yue Yu, Yuchen Zhuang, Rongzhi Zhang, Yu Meng, Jiaming Shen, Chao Zhang

Multilingual Sequence-to-Sequence Models for Hebrew NLP
Matan Eyal, Hila Noga, Roee Aharoni, Idan Szpektor, Reut Tsarfaty

Triggering Multi-Hop Reasoning for Question Answering in Language Models Using Soft Prompts and Random Walks
Kanishka Misra*, Cicero Nogueira dos Santos, Siamak Shakeri


Complex Reasoning in Natural Language
Wenting Zhao, Mor Geva, Bill Yuchen Lin, Michihiro Yasunaga, Aman Madaan, Tao Yu

Generating Text from Language Models
Afra Amini, Ryan Cotterell, John Hewitt, Clara Meister, Tiago Pimentel


Simple and Efficient Natural Language Processing (SustaiNLP)
Organizers include: Tal Schuster

Workshop on Online Abuse and Harms (WOAH)
Organizers include: Aida Mostafazadeh Davani

Document-Grounded Dialogue and Conversational Question Answering (DialDoc)
Organizers include: Roee Aharoni

NLP for Conversational AI
Organizers include: Abhinav Rastogi

Computation and Written Language (CAWL)
Organizers include: Kyle Gorman, Brian Roark, Richard Sproat

Computational Morphology and Phonology (SIGMORPHON)
Speakers include: Kyle Gorman

Workshop on Narrative Understanding (WNU)
Organizers include: Elizabeth Clark

* Work done while at Google

Source: Google AI Blog

Google at CVPR 2023

This week marks the beginning of the premier annual Computer Vision and Pattern Recognition conference (CVPR 2023), held in-person in Vancouver, BC (with additional virtual content). As a leader in computer vision research and a Platinum Sponsor, Google Research will have a strong presence across CVPR 2023 with 90 papers being presented at the main conference and active involvement in over 40 conference workshops and tutorials.

If you are attending CVPR this year, please stop by our booth to chat with our researchers who are actively exploring the latest techniques for application to various areas of machine perception. Our researchers will also be available to talk about and demo several recent efforts, including on-device ML applications with MediaPipe, strategies for differential privacy, neural radiance field technologies and much more.

You can also learn more about our research being presented at CVPR 2023 in the list below (Google affiliations in bold).

Board and organizing committee

Senior area chairs include: Cordelia Schmid, Ming-Hsuan Yang

Area chairs include: Andre Araujo, Anurag Arnab, Rodrigo Benenson, Ayan Chakrabarti, Huiwen Chang, Alireza Fathi, Vittorio Ferrari, Golnaz Ghiasi, Boqing Gong, Yedid Hoshen, Varun Jampani, Lu Jiang, Da-Cheng Jua, Dahun Kim, Stephen Lombardi, Peyman Milanfar, Ben Mildenhall, Arsha Nagrani, Jordi Pont-Tuset, Paul Hongsuck Seo, Fei Sha, Saurabh Singh, Noah Snavely, Kihyuk Sohn, Chen Sun, Pratul P. Srinivasan, Deqing Sun, Andrea Tagliasacchi, Federico Tombari, Jasper Uijlings

Publicity Chair: Boqing Gong

Demonstration Chair: Jonathan T. Barron

Program Advisory Board includes: Cordelia Schmid, Richard Szeliski


Best Paper Award candidates

MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures
Zhiqin Chen, Thomas Funkhouser, Peter Hedman, Andrea Tagliasacchi

DynIBaR: Neural Dynamic Image-Based Rendering
Zhengqi Li, Qianqian Wang, Forrester Cole, Richard Tucker, Noah Snavely

DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
Nataniel Ruiz*, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, Kfir Aberman

On Distillation of Guided Diffusion Models
Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans

Highlight papers

Connecting Vision and Language with Video Localized Narratives
Paul Voigtlaender, Soravit Changpinyo, Jordi Pont-Tuset, Radu Soricut, Vittorio Ferrari

MaskSketch: Unpaired Structure-Guided Masked Image Generation
Dina Bashkirova*, Jose Lezama, Kihyuk Sohn, Kate Saenko, Irfan Essa

SPARF: Neural Radiance Fields from Sparse and Noisy Poses
Prune Truong*, Marie-Julie Rakotosaona, Fabian Manhardt, Federico Tombari

MAGVIT: Masked Generative Video Transformer
Lijun Yu*, Yong Cheng, Kihyuk Sohn, Jose Lezama, Han Zhang, Huiwen Chang, Alexander Hauptmann, Ming-Hsuan Yang, Yuan Hao, Irfan Essa, Lu Jiang

Region-Aware Pretraining for Open-Vocabulary Object Detection with Vision Transformers
Dahun Kim, Anelia Angelova, Weicheng Kuo

I2MVFormer: Large Language Model Generated Multi-View Document Supervision for Zero-Shot Image Classification
Muhammad Ferjad Naeem, Gul Zain Khan, Yongqin Xian, Muhammad Zeshan Afzal, Didier Stricker, Luc Van Gool, Federico Tombari

Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization
Zifan Wang*, Nan Ding, Tomer Levinboim, Xi Chen, Radu Soricut

Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpainting (see blog post)
Su Wang, Chitwan Saharia, Ceslee Montgomery, Jordi Pont-Tuset, Shai Noy, Stefano Pellegrini, Yasumasa Onoe, Sarah Laszlo, David J. Fleet, Radu Soricut, Jason Baldridge, Mohammad Norouzi, Peter Anderson, William Cha

RUST: Latent Neural Scene Representations from Unposed Imagery
Mehdi S. M. Sajjadi, Aravindh Mahendran, Thomas Kipf, Etienne Pot, Daniel Duckworth, Mario Lučić, Klaus Greff

REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory (see blog post)
Ziniu Hu*, Ahmet Iscen, Chen Sun, Zirui Wang, Kai-Wei Chang, Yizhou Sun, Cordelia Schmid, David Ross, Alireza Fathi

RobustNeRF: Ignoring Distractors with Robust Losses
Sara Sabour, Suhani Vora, Daniel Duckworth, Ivan Krasin, David J. Fleet, Andrea Tagliasacchi


AligNeRF: High-Fidelity Neural Radiance Fields via Alignment-Aware Training
Yifan Jiang*, Peter Hedman, Ben Mildenhall, Dejia Xu, Jonathan T. Barron, Zhangyang Wang, Tianfan Xue*

BlendFields: Few-Shot Example-Driven Facial Modeling
Kacper Kania, Stephan Garbin, Andrea Tagliasacchi, Virginia Estellers, Kwang Moo Yi, Tomasz Trzcinski, Julien Valentin, Marek Kowalski

Enhancing Deformable Local Features by Jointly Learning to Detect and Describe Keypoints
Guilherme Potje, Felipe Cadar, Andre Araujo, Renato Martins, Erickson Nascimento

How Can Objects Help Action Recognition?
Xingyi Zhou, Anurag Arnab, Chen Sun, Cordelia Schmid

Hybrid Neural Rendering for Large-Scale Scenes with Motion Blur
Peng Dai, Yinda Zhang, Xin Yu, Xiaoyang Lyu, Xiaojuan Qi

IFSeg: Image-Free Semantic Segmentation via Vision-Language Model
Sukmin Yun, Seong Park, Paul Hongsuck Seo, Jinwoo Shin

Learning from Unique Perspectives: User-Aware Saliency Modeling (see blog post)
Shi Chen*, Nachiappan Valliappan, Shaolei Shen, Xinyu Ye, Kai Kohlhoff, Junfeng He

MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis
Tianhong Li*, Huiwen Chang, Shlok Kumar Mishra, Han Zhang, Dina Katabi, Dilip Krishnan

NeRF-Supervised Deep Stereo
Fabio Tosi, Alessio Tonioni, Daniele Gregorio, Matteo Poggi

Omnimatte3D: Associating Objects and their Effects in Unconstrained Monocular Video
Mohammed Suhail, Erika Lu, Zhengqi Li, Noah Snavely, Leon Sigal, Forrester Cole

OpenScene: 3D Scene Understanding with Open Vocabularies
Songyou Peng, Kyle Genova, Chiyu Jiang, Andrea Tagliasacchi, Marc Pollefeys, Thomas Funkhouser

PersonNeRF: Personalized Reconstruction from Photo Collections
Chung-Yi Weng, Pratul Srinivasan, Brian Curless, Ira Kemelmacher-Shlizerman

Prefix Conditioning Unifies Language and Label Supervision
Kuniaki Saito*, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister

Rethinking Video ViTs: Sparse Video Tubes for Joint Image and Video Learning (see blog post)
AJ Piergiovanni, Weicheng Kuo, Anelia Angelova

Burstormer: Burst Image Restoration and Enhancement Transformer
Akshay Dudhane, Syed Waqas Zamir, Salman Khan, Fahad Shahbaz Khan, Ming-Hsuan Yang

Decentralized Learning with Multi-Headed Distillation
Andrey Zhmoginov, Mark Sandler, Nolan Miller, Gus Kristiansen, Max Vladymyrov

GINA-3D: Learning to Generate Implicit Neural Assets in the Wild
Bokui Shen, Xinchen Yan, Charles R. Qi, Mahyar Najibi, Boyang Deng, Leonidas Guibas, Yin Zhou, Dragomir Anguelov

Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent with Learned Distance Functions
Yun He, Danhang Tang, Yinda Zhang, Xiangyang Xue, Yanwei Fu

Hi-LASSIE: High-Fidelity Articulated Shape and Skeleton Discovery from Sparse Image Ensemble
Chun-Han Yao*, Wei-Chih Hung, Yuanzhen Li, Michael Rubinstein, Ming-Hsuan Yang, Varun Jampani

Hyperbolic Contrastive Learning for Visual Representations beyond Objects
Songwei Ge, Shlok Mishra, Simon Kornblith, Chun-Liang Li, David Jacobs

Imagic: Text-Based Real Image Editing with Diffusion Models
Bahjat Kawar*, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang, Tali Dekel, Inbar Mosseri, Michal Irani

Incremental 3D Semantic Scene Graph Prediction from RGB Sequences
Shun-Cheng Wu, Keisuke Tateno, Nassir Navab, Federico Tombari

IPCC-TP: Utilizing Incremental Pearson Correlation Coefficient for Joint Multi-Agent Trajectory Prediction
Dekai Zhu, Guangyao Zhai, Yan Di, Fabian Manhardt, Hendrik Berkemeyer, Tuan Tran, Nassir Navab, Federico Tombari, Benjamin Busam

Learning to Generate Image Embeddings with User-Level Differential Privacy
Zheng Xu, Maxwell Collins, Yuxiao Wang, Liviu Panait, Sewoong Oh, Sean Augenstein, Ting Liu, Florian Schroff, H. Brendan McMahan

NoisyTwins: Class-Consistent and Diverse Image Generation Through StyleGANs
Harsh Rangwani, Lavish Bansal, Kartik Sharma, Tejan Karmali, Varun Jampani, Venkatesh Babu Radhakrishnan

NULL-Text Inversion for Editing Real Images Using Guided Diffusion Models
Ron Mokady*, Amir Hertz*, Kfir Aberman, Yael Pritch, Daniel Cohen-Or*

SCOOP: Self-Supervised Correspondence and Optimization-Based Scene Flow
Itai Lang*, Dror Aiger, Forrester Cole, Shai Avidan, Michael Rubinstein

Shape, Pose, and Appearance from a Single Image via Bootstrapped Radiance Field Inversion
Dario Pavllo*, David Joseph Tan, Marie-Julie Rakotosaona, Federico Tombari

TexPose: Neural Texture Learning for Self-Supervised 6D Object Pose Estimation
Hanzhi Chen, Fabian Manhardt, Nassir Navab, Benjamin Busam

TryOnDiffusion: A Tale of Two UNets
Luyang Zhu*, Dawei Yang, Tyler Zhu, Fitsum Reda, William Chan, Chitwan Saharia, Mohammad Norouzi, Ira Kemelmacher-Shlizerman

A New Path: Scaling Vision-and-Language Navigation with Synthetic Instructions and Imitation Learning
Aishwarya Kamath*, Peter Anderson, Su Wang, Jing Yu Koh*, Alexander Ku, Austin Waters, Yinfei Yang*, Jason Baldridge, Zarana Parekh

CLIPPO: Image-and-Language Understanding from Pixels Only
Michael Tschannen, Basil Mustafa, Neil Houlsby

Controllable Light Diffusion for Portraits
David Futschik, Kelvin Ritland, James Vecore, Sean Fanello, Sergio Orts-Escolano, Brian Curless, Daniel Sýkora, Rohit Pandey

CUF: Continuous Upsampling Filters
Cristina Vasconcelos, Cengiz Oztireli, Mark Matthews, Milad Hashemi, Kevin Swersky, Andrea Tagliasacchi

Improving Zero-Shot Generalization and Robustness of Multi-modal Models
Yunhao Ge*, Jie Ren, Andrew Gallagher, Yuxiao Wang, Ming-Hsuan Yang, Hartwig Adam, Laurent Itti, Balaji Lakshminarayanan, Jiaping Zhao

LOCATE: Localize and Transfer Object Parts for Weakly Supervised Affordance Grounding
Gen Li, Varun Jampani, Deqing Sun, Laura Sevilla-Lara

Nerflets: Local Radiance Fields for Efficient Structure-Aware 3D Scene Representation from 2D Supervision
Xiaoshuai Zhang, Abhijit Kundu, Thomas Funkhouser, Leonidas Guibas, Hao Su, Kyle Genova

Self-Supervised AutoFlow
Hsin-Ping Huang, Charles Herrmann, Junhwa Hur, Erika Lu, Kyle Sargent, Austin Stone, Ming-Hsuan Yang, Deqing Sun

Train-Once-for-All Personalization
Hong-You Chen*, Yandong Li, Yin Cui, Mingda Zhang, Wei-Lun Chao, Li Zhang

Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning (see blog post)
Antoine Yang*, Arsha Nagrani, Paul Hongsuck Seo, Antoine Miech, Jordi Pont-Tuset, Ivan Laptev, Josef Sivic, Cordelia Schmid

VILA: Learning Image Aesthetics from User Comments with Vision-Language Pretraining
Junjie Ke, Keren Ye, Jiahui Yu, Yonghui Wu, Peyman Milanfar, Feng Yang

You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model
Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu

Accidental Light Probes
Hong-Xing Yu, Samir Agarwala, Charles Herrmann, Richard Szeliski, Noah Snavely, Jiajun Wu, Deqing Sun

FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning
Yuanhao Xiong, Ruochen Wang, Minhao Cheng, Felix Yu, Cho-Jui Hsieh

FlexiViT: One Model for All Patch Sizes
Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic

Iterative Vision-and-Language Navigation
Jacob Krantz, Shurjo Banerjee, Wang Zhu, Jason Corso, Peter Anderson, Stefan Lee, Jesse Thomason

MoDi: Unconditional Motion Synthesis from Diverse Data
Sigal Raab, Inbal Leibovitch, Peizhuo Li, Kfir Aberman, Olga Sorkine-Hornung, Daniel Cohen-Or

Multimodal Prompting with Missing Modalities for Visual Recognition
Yi-Lun Lee, Yi-Hsuan Tsai, Wei-Chen Chiu, Chen-Yu Lee

Scene-Aware Egocentric 3D Human Pose Estimation
Jian Wang, Diogo Luvizon, Weipeng Xu, Lingjie Liu, Kripasindhu Sarkar, Christian Theobalt

ShapeClipper: Scalable 3D Shape Learning from Single-View Images via Geometric and CLIP-Based Consistency
Zixuan Huang, Varun Jampani, Ngoc Anh Thai, Yuanzhen Li, Stefan Stojanov, James M. Rehg

Improving Image Recognition by Retrieving from Web-Scale Image-Text Data
Ahmet Iscen, Alireza Fathi, Cordelia Schmid

JacobiNeRF: NeRF Shaping with Mutual Information Gradients
Xiaomeng Xu, Yanchao Yang, Kaichun Mo, Boxiao Pan, Li Yi, Leonidas Guibas

Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos
Ziqian Bai*, Feitong Tan, Zeng Huang, Kripasindhu Sarkar, Danhang Tang, Di Qiu, Abhimitra Meka, Ruofei Du, Mingsong Dou, Sergio Orts-Escolano, Rohit Pandey, Ping Tan, Thabo Beeler, Sean Fanello, Yinda Zhang

NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis
Allan Zhou, Mo Jin Kim, Lirui Wang, Pete Florence, Chelsea Finn

Pic2Word: Mapping Pictures to Words for Zero-Shot Composed Image Retrieval
Kuniaki Saito*, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister

SCADE: NeRFs from Space Carving with Ambiguity-Aware Depth Estimates
Mikaela Uy, Ricardo Martin Brualla, Leonidas Guibas, Ke Li

Structured 3D Features for Reconstructing Controllable Avatars
Enric Corona, Mihai Zanfir, Thiemo Alldieck, Eduard Gabriel Bazavan, Andrei Zanfir, Cristian Sminchisescu

Token Turing Machines
Michael S. Ryoo, Keerthana Gopalakrishnan, Kumara Kahatapitiya, Ted Xiao, Kanishka Rao, Austin Stone, Yao Lu, Julian Ibarz, Anurag Arnab

TruFor: Leveraging All-Round Clues for Trustworthy Image Forgery Detection and Localization
Fabrizio Guillaro, Davide Cozzolino, Avneesh Sud, Nicholas Dufour, Luisa Verdoliva

Video Probabilistic Diffusion Models in Projected Latent Space
Sihyun Yu, Kihyuk Sohn, Subin Kim, Jinwoo Shin

Visual Prompt Tuning for Generative Transfer Learning
Kihyuk Sohn, Yuan Hao, Jose Lezama, Luisa Polania, Huiwen Chang, Han Zhang, Irfan Essa, Lu Jiang

Zero-Shot Referring Image Segmentation with Global-Local Context Features
Seonghoon Yu, Paul Hongsuck Seo, Jeany Son

AVFormer: Injecting Vision into Frozen Speech Models for Zero-Shot AV-ASR (see blog post)
Paul Hongsuck Seo, Arsha Nagrani, Cordelia Schmid

DC2: Dual-Camera Defocus Control by Learning to Refocus
Hadi Alzayer, Abdullah Abuolaim, Leung Chun Chan, Yang Yang, Ying Chen Lou, Jia-Bin Huang, Abhishek Kar

Edges to Shapes to Concepts: Adversarial Augmentation for Robust Vision
Aditay Tripathi*, Rishubh Singh, Anirban Chakraborty, Pradeep Shenoy

MetaCLUE: Towards Comprehensive Visual Metaphors Research
Arjun R. Akula, Brendan Driscoll, Pradyumna Narayana, Soravit Changpinyo, Zhiwei Jia, Suyash Damle, Garima Pruthi, Sugato Basu, Leonidas Guibas, William T. Freeman, Yuanzhen Li, Varun Jampani

Multi-Realism Image Compression with a Conditional Generator
Eirikur Agustsson, David Minnen, George Toderici, Fabian Mentzer

NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image Priors
Congyue Deng, Chiyu Jiang, Charles R. Qi, Xinchen Yan, Yin Zhou, Leonidas Guibas, Dragomir Anguelov

On Calibrating Semantic Segmentation Models: Analyses and an Algorithm
Dongdong Wang, Boqing Gong, Liqiang Wang

Persistent Nature: A Generative Model of Unbounded 3D Worlds
Lucy Chai, Richard Tucker, Zhengqi Li, Phillip Isola, Noah Snavely

Rethinking Domain Generalization for Face Anti-spoofing: Separability and Alignment
Yiyou Sun*, Yaojie Liu, Xiaoming Liu, Yixuan Li, Wen-Sheng Chu

SINE: Semantic-Driven Image-Based NeRF Editing with Prior-Guided Editing Field
Chong Bao, Yinda Zhang, Bangbang Yang, Tianxing Fan, Zesong Yang, Hujun Bao, Guofeng Zhang, Zhaopeng Cui

Sequential Training of GANs Against GAN-Classifiers Reveals Correlated "Knowledge Gaps" Present Among Independently Trained GAN Instances
Arkanath Pathak, Nicholas Dufour

SparsePose: Sparse-View Camera Pose Regression and Refinement
Samarth Sinha, Jason Zhang, Andrea Tagliasacchi, Igor Gilitschenski, David Lindell

Teacher-Generated Spatial-Attention Labels Boost Robustness and Accuracy of Contrastive Models
Yushi Yao, Chang Ye, Gamaleldin F. Elsayed, Junfeng He


Computer Vision for Mixed Reality
Speakers include: Ira Kemelmacher-Shlizerman

Workshop on Autonomous Driving (WAD)
Speakers include: Chelsea Finn

Multimodal Content Moderation (MMCM)
Organizers include: Chris Bregler
Speakers include: Mevan Babakar

Medical Computer Vision (MCV)
Speakers include: Shekoofeh Azizi

VAND: Visual Anomaly and Novelty Detection
Speakers include: Yedid Hoshen, Jie Ren

Structural and Compositional Learning on 3D Data
Organizers include: Leonidas Guibas
Speakers include: Andrea Tagliasacchi, Fei Xia, Amir Hertz

Fine-Grained Visual Categorization (FGVC10)
Organizers include: Kimberly Wilber, Sara Beery
Panelists include: Hartwig Adam

XRNeRF: Advances in NeRF for the Metaverse
Organizers include: Jonathan T. Barron
Speakers include: Ben Poole

OmniLabel: Infinite Label Spaces for Semantic Understanding via Natural Language
Organizers include: Golnaz Ghiasi, Long Zhao
Speakers include: Vittorio Ferrari

Large Scale Holistic Video Understanding
Organizers include: David Ross
Speakers include: Cordelia Schmid

New Frontiers for Zero-Shot Image Captioning Evaluation (NICE)
Speakers include: Cordelia Schmid

Computational Cameras and Displays (CCD)
Organizers include: Ulugbek Kamilov
Speakers include: Mauricio Delbracio

Gaze Estimation and Prediction in the Wild (GAZE)
Organizers include: Thabo Beele
Speakers include: Erroll Wood

Face and Gesture Analysis for Health Informatics (FGAHI)
Speakers include: Daniel McDuff

Computer Vision for Animal Behavior Tracking and Modeling (CV4Animals)
Organizers include: Sara Beery
Speakers include: Arsha Nagrani

3D Vision and Robotics
Speakers include: Pete Florence

End-to-End Autonomous Driving: Perception, Prediction, Planning and Simulation (E2EAD)
Organizers include: Anurag Arnab

End-to-End Autonomous Driving: Emerging Tasks and Challenges
Speakers include: Sergey Levine

Multi-Modal Learning and Applications (MULA)
Speakers include: Aleksander Hołyński

Synthetic Data for Autonomous Systems (SDAS)
Speakers include: Lukas Hoyer

Vision Datasets Understanding
Organizers include: José Lezama
Speakers include: Vijay Janapa Reddi

Precognition: Seeing Through the Future
Organizers include: Utsav Prabhu

New Trends in Image Restoration and Enhancement (NTIRE)
Organizers include: Ming-Hsuan Yang

Generative Models for Computer Vision
Speakers include: Ben Mildenhall, Andrea Tagliasacchi

Adversarial Machine Learning on Computer Vision: Art of Robustness
Organizers include: Xinyun Chen
Speakers include: Deqing Sun

Media Forensics
Speakers include: Nicholas Carlini

Tracking and Its Many Guises: Tracking Any Object in Open-World
Organizers include: Paul Voigtlaender

3D Scene Understanding for Vision, Graphics, and Robotics
Speakers include: Andy Zeng

Computer Vision for Physiological Measurement (CVPM)
Organizers include: Daniel McDuff

Affective Behaviour Analysis In-the-Wild
Organizers include: Stefanos Zafeiriou

Ethical Considerations in Creative Applications of Computer Vision (EC3V)
Organizers include: Rida Qadri, Mohammad Havaei, Fernando Diaz, Emily Denton, Sarah Laszlo, Negar Rostamzadeh, Pamela Peter-Agbia, Eva Kozanecka

VizWiz Grand Challenge: Describing Images and Videos Taken by Blind People
Speakers include: Haoran Qi

Efficient Deep Learning for Computer Vision (see blog post)
Organizers include: Andrew Howard, Chas Leichner
Speakers include: Andrew Howard

Visual Copy Detection
Organizers include: Priya Goyal

Learning 3D with Multi-View Supervision (3DMV)
Speakers include: Ben Poole

Image Matching: Local Features and Beyond
Organizers include: Eduard Trulls

Vision for All Seasons: Adverse Weather and Lightning Conditions (V4AS)
Organizers include: Lukas Hoyer

Transformers for Vision (T4V)
Speakers include: Cordelia Schmid, Huiwen Chang

Scholars vs Big Models — How Can Academics Adapt?
Organizers include: Sara Beery
Speakers include: Jonathan T. Barron, Cordelia Schmid

ScanNet Indoor Scene Understanding Challenge
Speakers include: Tom Funkhouser

Computer Vision for Microscopy Image Analysis
Speakers include: Po-Hsuan Cameron Chen

Embedded Vision
Speakers include: Rahul Sukthankar

Sight and Sound
Organizers include: Arsha Nagrani, William Freeman

AI for Content Creation
Organizers include: Deqing Sun, Huiwen Chang, Lu Jiang

Speakers include: Ben Mildenhall, Tim Salimans, Yuanzhen Li

Computer Vision in the Wild
Organizers include: Xiuye Gu, Neil Houlsby
Speakers include: Boqing Gong, Anelia Angelova

Visual Pre-Training for Robotics
Organizers include: Mathilde Caron

Omnidirectional Computer Vision
Organizers include: Yi-Hsuan Tsai


All Things ViTs: Understanding and Interpreting Attention in Vision
Hila Chefer, Sayak Paul

Recent Advances in Anomaly Detection
Guansong Pang, Joey Tianyi Zhou, Radu Tudor Ionescu, Yu Tian, Kihyuk Sohn

Contactless Healthcare Using Cameras and Wireless Sensors
Wenjin Wang, Xuyu Wang, Jun Luo, Daniel McDuff

Object Localization for Free: Going Beyond Self-Supervised Learning
Oriane Simeoni, Weidi Xie, Thomas Kipf, Patrick Pérez

Prompting in Vision
Kaiyang Zhou, Ziwei Liu, Phillip Isola, Hyojin Bahng, Ludwig Schmidt, Sarah Pratt, Denny Zhou

* Work done while at Google

Source: Google AI Blog

Google at ICLR 2023

The Eleventh International Conference on Learning Representations (ICLR 2023) is being held this week as a hybrid event in Kigali, Rwanda. We are proud to be a Diamond Sponsor of ICLR 2023, a premier conference on deep learning, where Google researchers contribute at all levels. This year we are presenting over 100 papers and are actively involved in organizing and hosting a number of different events, including workshops and interactive sessions.

If you’re registered for ICLR 2023, we hope you’ll visit the Google booth to learn more about the exciting work we’re doing across topics spanning representation and reinforcement learning, theory and optimization, social impact, safety and privacy, and applications from generative AI to speech and robotics. Continue below to find the many ways in which Google researchers are engaged at ICLR 2023, including workshops, papers, posters and talks (Google affiliations in bold).

Board and Organizing Committee

Board Members include: Shakir Mohamed, Tara Sainath

Senior Program Chairs include: Been Kim

Workshop Chairs include: Aisha Walcott-Bryant, Rose Yu

Diversity, Equity & Inclusion Chairs include: Rosanne Liu

Outstanding Paper awards

Emergence of Maps in the Memories of Blind Navigation Agents
Erik Wijmans, Manolis Savva, Irfan Essa, Stefan Lee, Ari S. Morcos, Dhruv Batra

DreamFusion: Text-to-3D Using 2D Diffusion
Ben Poole, Ajay Jain, Jonathan T. Barron, Ben Mildenhall

Keynote speaker

Learned Optimizers: Why They're the Future, Why They’re Hard, and What They Can Do Now
Jascha Sohl-Dickstein


Kaggle@ICLR 2023: ML Solutions in Africa
Organizers include: Julia Elliott, Phil Culliton, Ray Harvey
Facilitators: Julia Elliot, Walter Reade

Reincarnating Reinforcement Learning (Reincarnating RL)
Organizers include: Rishabh Agarwal, Ted Xiao, Max Schwarzer
Speakers include: Sergey Levine
Panelists include: Marc G. Bellemare, Sergey Levine

Trustworthy and Reliable Large-Scale Machine Learning Models
Organizers include: Sanmi Koyejo
Speakers include: Nicholas Carlini

Physics for Machine Learning (Physics4ML)
Speakers include: Yasaman Bahri

AI for Agent-Based Modelling Community (AI4ABM)
Organizers include: Pablo Samuel Castro

Mathematical and Empirical Understanding of Foundation Models (ME-FoMo)
Organizers include: Mathilde Caron, Tengyu Ma, Hanie Sedghi
Speakers include: Yasaman Bahri, Yann Dauphin

Neurosymbolic Generative Models 2023 (NeSy-GeMs)
Organizers include: Kevin Ellis
Speakers include: Daniel Tarlow, Tuan Anh Le

What Do We Need for Successful Domain Generalization?
Panelists include: Boqing Gong

The 4th Workshop on Practical ML for Developing Countries: Learning Under Limited/Low Resource Settings
Keynote Speaker: Adji Bousso Dieng

Machine Learning for Remote Sensing
Speakers include: Abigail Annkah

Multimodal Representation Learning (MRL): Perks and Pitfalls
Organizers include: Petra Poklukar
Speakers include: Arsha Nagrani

Pitfalls of Limited Data and Computation for Trustworthy ML
Organizers include: Prateek Jain
Speakers include: Nicholas Carlini, Praneeth Netrapalli

Sparsity in Neural Networks: On Practical Limitations and Tradeoffs Between Sustainability and Efficiency
Organizers include: Trevor Gale, Utku Evci
Speakers include: Aakanksha Chowdhery, Jeff Dean

Time Series Representation Learning for Health
Speakers include: Katherine Heller

Deep Learning for Code (DL4C)
Organizers include: Gabriel Orlanski
Speakers include: Alex Polozov, Daniel Tarlow

Affinity Workshops

Tiny Papers Showcase Day (a DEI initiative)
Organizers include: Rosanne Liu


Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics for Advection-Dominated Systems
Zhong Yi Wan, Leonardo Zepeda-Nunez, Anudhyan Boral, Fei Sha

Quantifying Memorization Across Neural Language Models
Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramer, Chiyuan Zhang

Emergence of Maps in the Memories of Blind Navigation Agents (Outstanding Paper Award)
Erik Wijmans, Manolis Savva, Irfan Essa, Stefan Lee, Ari S. Morcos, Dhruv Batra

Offline Q-Learning on Diverse Multi-task Data Both Scales and Generalizes (see blog post)
Aviral Kumar, Rishabh Agarwal, Xingyang Geng, George Tucker, Sergey Levine

ReAct: Synergizing Reasoning and Acting in Language Models (see blog post)
Shunyu Yao*, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R. Narasimhan, Yuan Cao

Prompt-to-Prompt Image Editing with Cross-Attention Control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, Daniel Cohen-Or

DreamFusion: Text-to-3D Using 2D Diffusion (Outstanding Paper Award)
Ben Poole, Ajay Jain, Jonathan T. Barron, Ben Mildenhall

A System for Morphology-Task Generalization via Unified Representation and Behavior Distillation
Hiroki Furuta, Yusuke Iwasawa, Yutaka Matsuo, Shixiang Shane Gu

Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier
Pierluca D'Oro, Max Schwarzer, Evgenii Nikishin, Pierre-Luc Bacon, Marc G Bellemare, Aaron Courville

Dichotomy of Control: Separating What You Can Control from What You Cannot
Sherry Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum

Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
Michał Zawalski, Michał Tyrolski, Konrad Czechowski, Tomasz Odrzygóźdź, Damian Stachura, Piotr Piekos, Yuhuai Wu, Łukasz Kucinski, Piotr Miłos

The Trade-Off Between Universality and Label Efficiency of Representations from Contrastive Learning
Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha

Sparsity-Constrained Optimal Transport
Tianlin Liu*, Joan Puigcerver, Mathieu Blondel

Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask?
Mansheej Paul, Feng Chen, Brett W. Larsen, Jonathan Frankle, Surya Ganguli, Gintare Karolina Dziugaite

Extreme Q-Learning: MaxEnt RL without Entropy
Divyansh Garg, Joey Hejna, Matthieu Geist, Stefano Ermon

Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs
Albert Qiaochu Jiang, Sean Welleck, Jin Peng Zhou, Timothee Lacroix, Jiacheng Liu, Wenda Li, Mateja Jamnik, Guillaume Lample, Yuhuai Wu

SimPer: Simple Self-Supervised Learning of Periodic Targets
Yuzhe Yang, Xin Liu, Jiang Wu, Silviu Borac, Dina Katabi, Ming-Zher Poh, Daniel McDuff

Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language
Andy Zeng, Maria Attarian, Brian Ichter, Krzysztof Marcin Choromanski, Adrian Wong, Stefan Welker, Federico Tombari, Aveek Purohit, Michael S. Ryoo, Vikas Sindhwani, Johnny Lee, Vincent Vanhoucke, Pete Florence

What Learning Algorithm Is In-Context Learning? Investigations with Linear Models
Ekin Akyurek*, Dale Schuurmans, Jacob Andreas, Tengyu Ma*, Denny Zhou

Preference Transformer: Modeling Human Preferences Using Transformers for RL
Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee

Iterative Patch Selection for High-Resolution Image Recognition
Benjamin Bergner, Christoph Lippert, Aravindh Mahendran

Open-Vocabulary Object Detection upon Frozen Vision and Language Models
Weicheng Kuo, Yin Cui, Xiuye Gu, AJ Piergiovanni, Anelia Angelova

(Certified!!) Adversarial Robustness for Free!
Nicholas Carlini, Florian Tramér, Krishnamurthy (Dj) Dvijotham, Leslie Rice, Mingjie Sun, J. Zico Kolter

REPAIR: REnormalizing Permuted Activations for Interpolation Repair
Keller Jordan, Hanie Sedghi, Olga Saukh, Rahim Entezari, Behnam Neyshabur

Discrete Predictor-Corrector Diffusion Models for Image Synthesis
José Lezama, Tim Salimans, Lu Jiang, Huiwen Chang, Jonathan Ho, Irfan Essa

Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks
Sravanti Addepalli, Anshul Nasery, Praneeth Netrapalli, Venkatesh Babu R., Prateek Jain

An Exact Poly-time Membership-Queries Algorithm for Extracting a Three-Layer ReLU Network
Amit Daniely, Elad Granot

Language Models Are Multilingual Chain-of-Thought Reasoners
Freda Shi, Mirac Suzgun, Markus Freitag, Xuezhi Wang, Suraj Srivats, Soroush Vosoughi, Hyung Won Chung, Yi Tay, Sebastian Ruder, Denny Zhou, Dipanjan Das, Jason Wei

Scaling Forward Gradient with Local Losses
Mengye Ren*, Simon Kornblith, Renjie Liao, Geoffrey Hinton

Treeformer: Dense Gradient Trees for Efficient Attention Computation
Lovish Madaan, Srinadh Bhojanapalli, Himanshu Jain, Prateek Jain

LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification
Sharath Girish, Kamal Gupta, Saurabh Singh, Abhinav Shrivastava

DiffusER: Diffusion via Edit-Based Reconstruction
Machel Reid, Vincent J. Hellendoorn, Graham Neubig

Leveraging Unlabeled Data to Track Memorization
Mahsa Forouzesh, Hanie Sedghi, Patrick Thiran

A Mixture-of-Expert Approach to RL-Based Dialogue Management
Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier

Easy Differentially Private Linear Regression
Kareem Amin, Matthew Joseph, Monica Ribero, Sergei Vassilvitskii

KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals
Sandeep Silwal*, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Mehran Kazemi

Massively Scaling Heteroscedastic Classifiers
Mark Collier, Rodolphe Jenatton, Basil Mustafa, Neil Houlsby, Jesse Berent, Effrosyni Kokiopoulou

The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
Zonglin Li, Chong You, Srinadh Bhojanapalli, Daliang Li, Ankit Singh Rawat, Sashank J. Reddi, Ke Ye, Felix Chern, Felix Yu, Ruiqi Guo, Sanjiv Kumar

Compositional Semantic Parsing with Large Language Models
Andrew Drozdov, Nathanael Scharli, Ekin Akyurek, Nathan Scales, Xinying Song, Xinyun Chen, Olivier Bousquet, Denny Zhou

Extremely Simple Activation Shaping for Out-of-Distribution Detection
Andrija Djurisic, Nebojsa Bozanic, Arjun Ashok, Rosanne Liu

Long Range Language Modeling via Gated State Spaces
Harsh Mehta, Ankit Gupta, Ashok Cutkosky, Behnam Neyshabur

Investigating Multi-task Pretraining and Generalization in Reinforcement Learning
Adrien Ali Taiga, Rishabh Agarwal, Jesse Farebrother, Aaron Courville, Marc G. Bellemare

Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets
Edo Cohen-Karlik, Itamar Menuhin-Gruman, Raja Giryes, Nadav Cohen, Amir Globerson

Weighted Ensemble Self-Supervised Learning
Yangjun Ruan*, Saurabh Singh, Warren Morningstar, Alexander A. Alemi, Sergey Ioffe, Ian Fischer, Joshua V. Dillon

Calibrating Sequence Likelihood Improves Conditional Language Generation
Yao Zhao, Misha Khalman, Rishabh Joshi, Shashi Narayan, Mohammad Saleh, Peter J. Liu

SMART: Sentences as Basic Units for Text Evaluation
Reinald Kim Amplayo, Peter J. Liu, Yao Zhao, Shashi Narayan

Leveraging Importance Weights in Subset Selection
Gui Citovsky, Giulia DeSalvo, Sanjiv Kumar, Srikumar Ramalingam, Afshin Rostamizadeh, Yunjuan Wang*

Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks
Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare

An Extensible Multi-modal Multi-task Object Dataset with Materials
Trevor Standley, Ruohan Gao, Dawn Chen, Jiajun Wu, Silvio Savarese

Measuring Forgetting of Memorized Training Examples
Matthew Jagielski, Om Thakkar, Florian Tramér, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, Chiyuan Zhang

Bidirectional Language Models Are Also Few-Shot Learners
Ajay Patel, Bryan Li, Mohammad Sadegh Rasooli, Noah Constant, Colin Raffel, Chris Callison-Burch

Is Attention All That NeRF Needs?
Mukund Varma T., Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang

Automating Nearest Neighbor Search Configuration with Constrained Optimization
Philip Sun, Ruiqi Guo, Sanjiv Kumar

Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions
David Bieber, Rishab Goel, Daniel Zheng, Hugo Larochelle, Daniel Tarlow

Composing Ensembles of Pre-trained Models via Iterative Consensus
Shuang Li, Yilun Du, Joshua B. Tenenbaum, Antonio Torralba, Igor Mordatch

Λ-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection Among Cells
Sajad Movahedi, Melika Adabinejad, Ayyoob Imani, Arezou Keshavarz, Mostafa Dehghani, Azadeh Shakery, Babak N. Araabi

Blurring Diffusion Models
Emiel Hoogeboom, Tim Salimans

Part-Based Models Improve Adversarial Robustness
Chawin Sitawarin, Kornrapat Pongmala, Yizheng Chen, Nicholas Carlini, David Wagner

Learning in Temporally Structured Environments
Matt Jones, Tyler R. Scott, Mengye Ren, Gamaleldin ElSayed, Katherine Hermann, David Mayo, Michael C. Mozer

SlotFormer: Unsupervised Visual Dynamics Simulation with Object-Centric Models
Ziyi Wu, Nikita Dvornik, Klaus Greff, Thomas Kipf, Animesh Garg

Robust Algorithms on Adaptive Inputs from Bounded Adversaries
Yeshwanth Cherapanamjeri, Sandeep Silwal, David P. Woodruff, Fred Zhang, Qiuyi (Richard) Zhang, Samson Zhou

Agnostic Learning of General ReLU Activation Using Gradient Descent
Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan

Analog Bits: Generating Discrete Data Using Diffusion Models with Self-Conditioning
Ting Chen, Ruixiang Zhang, Geoffrey Hinton

Any-Scale Balanced Samplers for Discrete Space
Haoran Sun*, Bo Dai, Charles Sutton, Dale Schuurmans, Hanjun Dai

Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation
Ziqi Wang*, Yuexin Wu, Frederick Liu, Daogao Liu, Le Hou, Hongkun Yu, Jing Li, Heng Ji

Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD
Konstantinos E. Nikolakakis, Farzin Haddadpour, Amin Karbasi, Dionysios S. Kalogerias

Causal Estimation for Text Data with (Apparent) Overlap Violations
Lin Gui, Victor Veitch

Contrastive Learning Can Find an Optimal Basis for Approximately View-Invariant Functions
Daniel D. Johnson, Ayoub El Hanchi, Chris J. Maddison

Differentially Private Adaptive Optimization with Delayed Preconditioners
Tian Li, Manzil Zaheer, Ziyu Liu, Sashank Reddi, Brendan McMahan, Virginia Smith

Distributionally Robust Post-hoc Classifiers Under Prior Shifts
Jiaheng Wei*, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar

Human Alignment of Neural Network Representations
Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith

Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data
Spencer Frei, Gal Vardi, Peter Bartlett, Nathan Srebro, Wei Hu

Koopman Neural Operator Forecaster for Time-Series with Temporal Distributional Shifts
Rui Wang*, Yihe Dong, Sercan Ö. Arik, Rose Yu

Latent Variable Representation for Reinforcement Learning
Tongzheng Ren, Chenjun Xiao, Tianjun Zhang, Na Li, Zhaoran Wang, Sujay Sanghavi, Dale Schuurmans, Bo Dai

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
Denny Zhou, Nathanael Scharli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc Le, Ed Chi

Mind's Eye: Grounded Language Model Reasoning Through Simulation
Ruibo Liu, Jason Wei, Shixiang Shane Gu, Te-Yen Wu, Soroush Vosoughi, Claire Cui, Denny Zhou, Andrew M. Dai

MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models
Chenglin Yang*, Siyuan Qiao, Qihang Yu, Xiaoding Yuan, Yukun Zhu, Alan Yuille, Hartwig Adam, Liang-Chieh Chen

Novel View Synthesis with Diffusion Models
Daniel Watson, William Chan, Ricardo Martin-Brualla, Jonathan Ho, Andrea Tagliasacchi, Mohammad Norouzi

On Accelerated Perceptrons and Beyond
Guanghui Wang, Rafael Hanashiro, Etash Guha, Jacob Abernethy

On Compositional Uncertainty Quantification for Seq2seq Graph Parsing
Zi Lin*, Du Phan, Panupong Pasupat, Jeremiah Liu, Jingbo Shang

On the Robustness of Safe Reinforcement Learning Under Observational Perturbations
Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao

Online Low Rank Matrix Completion
Prateek Jain, Soumyabrata Pal

Out-of-Distribution Detection and Selective Generation for Conditional Language Models
Jie Ren, Jiaming Luo, Yao Zhao, Kundan Krishna*, Mohammad Saleh, Balaji Lakshminarayanan, Peter J. Liu

PaLI: A Jointly-Scaled Multilingual Language-Image Model
Xi Chen, Xiao Wang, Soravit Changpinyo, AJ Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Nan Ding, Keran Rong, Hassan Akbari, Gaurav Mishra, Linting Xue, Ashish V. Thapliyal, James Bradbury, Weicheng Kuo, Mojtaba Seyedhosseini, Chao Jia, Burcu Karagol Ayan, Carlos Riquelme Ruiz, Andreas Peter Steiner, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut

Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions
Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro*, Julius Kunze*, Dumitru Erhan

Promptagator: Few-Shot Dense Retrieval from 8 Examples
Zhuyun Dai, Vincent Y. Zhao, Ji Ma, Yi Luan, Jianmo Ni, Jing Lu, Anton Bakalov, Kelvin Guu, Keith B. Hall, Ming-Wei Chang

Pushing the Accuracy-Group Robustness Frontier with Introspective Self-Play
Jeremiah Zhe Liu, Krishnamurthy Dj Dvijotham, Jihyeon Lee, Quan Yuan, Balaji Lakshminarayanan, Deepak Ramachandran

Re-Imagen: Retrieval-Augmented Text-to-Image Generator Wenhu Chen, Hexiang Hu, Chitwan Saharia, William W. Cohen

Recitation-Augmented Language Models
Zhiqing Sun, Xuezhi Wang, Yi Tay, Yiming Yang, Denny Zhou

Regression with Label Differential Privacy
Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash Varadarajan, Chiyuan Zhang

Revisiting the Entropy Semiring for Neural Speech Recognition
Oscar Chang, Dongseong Hwang, Olivier Siohan

Robust Active Distillation
Cenk Baykal, Khoa Trinh, Fotis Iliopoulos, Gaurav Menghani, Erik Vee

Score-Based Continuous-Time Discrete Diffusion Models
Haoran Sun*, Lijun Yu, Bo Dai, Dale Schuurmans, Hanjun Dai

Self-Consistency Improves Chain of Thought Reasoning in Language Models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou

Self-Supervision Through Random Segments with Autoregressive Coding (RandSAC)
Tianyu Hua, Yonglong Tian, Sucheng Ren, Michalis Raptis, Hang Zhao, Leonid Sigal

Serving Graph Compression for Graph Neural Networks
Si Si, Felix Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar

Sequential Attention for Feature Selection
Taisuke Yasuda*, MohammadHossein Bateni, Lin Chen, Matthew Fahrbach, Gang Fu, Vahab Mirrokni

Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints
Aran Komatsuzaki*, Joan Puigcerver, James Lee-Thorp, Carlos Riquelme, Basil Mustafa, Joshua Ainslie, Yi Tay, Mostafa Dehghani, Neil Houlsby

Spectral Decomposition Representation for Reinforcement Learning
Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph Gonzalez, Dale Schuurmans, Bo Dai

Spotlight: Mobile UI Understanding Using Vision-Language Models with a Focus (see blog post)
Gang Li, Yang Li

Supervision Complexity and Its Role in Knowledge Distillation
Hrayr Harutyunyan*, Ankit Singh Rawat, Aditya Krishna Menon, Seungyeon Kim, Sanjiv Kumar

Teacher Guided Training: An Efficient Framework for Knowledge Transfer
Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar

TEMPERA: Test-Time Prompt Editing via Reinforcement Learning
Tianjun Zhang, Xuezhi Wang, Denny Zhou, Dale Schuurmans, Joseph E. Gonzalez

UL2: Unifying Language Learning Paradigms
Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Xavier Garcia, Jason Wei, Xuezhi Wang, Hyung Won Chung, Dara Bahri, Tal Schuster, Steven Zheng, Denny Zhou, Neil Houlsby, Donald Metzler

* Work done while at Google

Source: Google AI Blog

Google at NeurIPS 2022

This week marks the beginning of the 36th annual Conference on Neural Information Processing Systems (NeurIPS 2022), the biggest machine learning conference of the year, which is being held in New Orleans, LA. NeurIPS 2022 will be held in person with additional options for virtual attendees, and includes invited talks, demonstrations and presentations of some of the latest in machine learning research. This year, NeurIPS is also offering a new track, called Spotlight Papers, which will provide opportunities to highlight papers presented in prestigious journals that would otherwise not have been eligible for submission.

Google is proud to be a Diamond level sponsor of NeurIPS this year and will have a significant presence year with more than 175 accepted papers, additionally contributing to and learning from the broader academic research community through numerous talks, posters, workshops, and tutorials. You can learn more about our work being presented in the list below (Google affiliations highlighted in bold).

Organizing Committee

General Chairs includes: Sanmi Koyejo

Program Chairs include: Alekh Agarwal

Workshop Chairs include: Hanie Sedghi

Tutorial Chairs include: Adji Bousso Dieng, Jessica Schrouff

Affinity Workshop Chair: Adji Bousso Dieng, Jessica Schrouff

Program Committee, Senior Area Chairs include: Corinna Cortes, Claudio Gentile, Mohammad Ghavamzadeh, Amir Globerson, Elad Hazan, Katherine Heller, Satyen Kale, Been Kim, Sanjiv Kumar, Hugo Larochelle, Sergey Levine, Yishay Mansour, Mehryar Mohri, Tara Sainath, Dale Schuurmans, Daniel Tarlow

NeurIPS Foundation Board Secretary: Michael Mozer

NeurIPS Foundation Board Members include: Corinna Cortes, Isabelle Guyon, Sanmi Koyejo, Hugo Larochelle

NeurIPS Foundation Advisory Board include: Peter Bartlett, Zoubin Ghahramani, John C. Platt, Fernando Pereira, Dale Schuurmans

Keynote Speakers

The Data-Centric Era: How ML is Becoming an Experimental Science
Isabelle Guyon

The Forward-Forward Algorithm for Training Deep Neural Networks
Geoffrey Hinton

Outstanding Paper Award

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, Mohammad Norouzi

EXPO Day Workshops

Graph Neural Networks in Tensorflow: A Practical Guide
Workshop Organizers include: Bryan Perozzi, Sami Abu-el-Haija

A Hands-On Introduction to Tensorflow and Jax
Workshop Organizers include: Josh Gordon

Affinity Workshops

LatinX in AI (LXAI)
Platinum Sponsor
Networking & Social Chairs include: Andres Muñoz Medina
Program Committee includes: Johan Obando Ceron

Queer in AI
Panelists include: Sara Beery, Talia Ringer

Women in Machine Learning (WiML)
Platinum Sponsor
Workshop Organizers and Mentorship Chairs include: Beliz Gunel
Mentors include: Adam Roberts, Eleni Triantafillou, Zelda Mariet, Clara Hu, Rosanne Liu, Alekh Agarwal, Vinod Prabhakaran, Rose Yu, Katherine Heller


New in ML
Workshop Organizers include: Isabelle Guyon

AI for Accelerated Materials Design (AI4Mat)
Workshop Organizers include: Benjamin Sanchez-Lengeling

All Things Attention: Bridging Different Perspectives on Attention
Invited Speakers and Panelists include: Vidhya Navalpakkam

Efficient Natural Language and Speech Processing (ENLSP-II): The Future of Pre-trained Models
Invited Speakers include: Tara Sainath, Anna Huang
Invited Panelists include: Mohammad Norouzi
Program Committee includes: Wenhu Chen

Federated Learning: Recent Advances and New Challenges
Program Committee includes: Kallista Bonawitz, Zachary Charles, Wenshuo Guo, Peter Kairouz, Zhaozhuo Xu, Zheng Xu

Gaussian Processes, Spatiotemporal Modeling, and Decision-Making Systems
Workshop Organizers include: Zi Wang
Invited Speakers include: Jasper Snoek, Carolina Osorio
Advisory Board includes: Zoubin Ghahramani

Has it Trained Yet? A Workshop for Algorithmic Efficiency in Practical Neural Network Training
Workshop Organizers include: Zachary Nado, George Dahl, Naman Agarwal, Aakanksha Chowdhery
Invited Speakers include: Aakanksha Chowdhery, Priya Goyal

Human in the Loop Learning (HiLL)
Workshop Organizers include: Fisher Yu, Vittorio Ferrari
Invited Speakers include: Dorsa Singh, Igor Mordatch, Ding Zhao

INTERPOLATE — First Workshop on Interpolation Regularizers and Beyond
Workshop Organizers include: Yann Dauphin
Invited Speakers include: Chelsea Finn
Panelists include: Chelsea Finn, Dustin Tran
Program Committee includes: Wang Chen, Kimin Lee

LaReL: Language and Reinforcement Learning
Invited Speakers include: Dorsa Singh, Igor Mordatch

Medical Imaging Meets NeurIPS
Program Committee includes: Chenyu You

Memory in Artificial and Real Intelligence (MemARI)
Program Committee includes: Benjamin Eysenbach, Otilia Stretcu

Workshop Organizers include: Eleni Triantafillou
Invited Speakers include: Lucas Byer, Chelsea Finn
Program Committee includes: Ishita Dasgupta, Praneet Dutta, Benjamin Eysenbach, Maximilian Igl, Louis Kirsch, Parsa Mahmoudieh, Marc Pickett, Eleni Triantafillou

New Frontiers in Graph Learning (GLFrontiers)
Workshop Organizers include: Hanjun Dai

Offline Reinforcement Learning Workshop: Offline RL as a "Launchpad"
Workshop Organizers include: Rishabh Agarwal, Aviral Kumar, George Tucker
Invited Speakers include: Dorsa Sadigh

Score-Based Methods
Invited Speakers include: Mohammad Norouzi
Invited Panelists include: Jascha Sohl-Dickstein

Synthetic Data for Empowering ML Research
Invited Speakers include: Mehryar Mohri
Invited Panelists include: Katrina Ligett
Program Committee includes: Jinsung Yoon

Table Representation Learning
Workshop Organizers include: Pengcheng Yin
Invited Speakers include: Xinyun Chen, Carsten Binnig
Panelists include: Julian Eisenschlos
Program Committee includes: Wenhu Chen, Xinyun Chen, Beliz Gunel

A Causal View on Dynamical Systems
Program Committee includes: Rose Yu

Algorithmic Fairness Through the Lens of Causality and Privacy
Workshop Organizers include: Awa Dieng
Invited Speakers include: Nicolas Papernot
Roundtable Leads include: David Madras, Negar Rostamzadeh, Nyalleng Moroosi
Program Committee includes: Matt Kusner

Broadening Research Collaborations in ML
Workshop Organizers include: Rosanne Liu, Pablo Samuel Castro, Sunipa Dev

Decentralization and Trustworthy Machine Learning in Web3: Methodologies, Platforms, and Applications
Invited Speakers include: Peter Kairouz

Distribution Shifts (DistShift): Connecting Methods and Applications
Workshop Organizers include: Becca Roelofs, Chelsea Finn, Jacob Eisenstein, Pang Wei Koh
Invited Speakers include: Sarah Beery

Foundation Models for Decision Making
Workshop Organizers include: Sherry Yang, Yilun Du, Igor Mordatch, Shixiang Shane Gu,Ofir Nachum
Invited Speakers include: Dorsa Sadigh, Dale Schuurmans, Machel Reid
Program Committee includes: Bo Dai, Aleksandra Faust, Hiroki Furuta, Kati Goshvadi, Izzeddin Gur, Austin Huang, Kimin Lee, Kuang-Huei Lee, Lisa Lee, Yingjie Miao, Jordi Orbay, Ted Xiao

Gaze Meets ML
Program Committee includes: Peter Mattson, Mehdi Moradi

I Can’t Believe It’s Not Better: Understanding Deep Learning Through Empirical Falsification
Workshop Organizers include: Javier Antorán
Panelists include: Kevin Murphy

Interactive Learning for Natural Language Processing
Invited Speakers include: Anca Dragan
Program Committees include: Julia Kreutzer, Shunyu Yao

Machine Learning and the Physical Sciences
Workshop Organizers include: Adji Bousso Dieng
Invited Speakers include: Ekin Doğuş Çubuk

Machine Learning for Systems
Workshop Organizers include: Martin Maas, Azade Nova, Dan Zhang
Invited Speakers include: Jeff Dean
Program Committee includes: Milad Hashemi, Kevin Swersky

Machine Learning in Structural Biology
Invited Speakers include: David Fleet

MATH-AI: Toward Human-Level Mathematical Reasoning
Workshop Organizers include: Swaroop Mishra, Yuhuai Wu
Invited Speakers include: Talia Ringer

OPT 2022: Optimization for Machine Learning
Workshop Organizers include: Courtney Paquette

Reinforcement Learning for Real Life (RL4RealLife)
Workshop Organizers include: Minmin Chen
Invited Panelists include: Pablo Samuel Castro
Program Committee includes: Victor Carbune, Bo Chang, Yinlam Chow, Konstantina Christakopoulou, Bo Dai, Hanjun Dai, Aleksandra Faust, Joshua Greaves‎, Chih-wei Hsu, Rahul Kidambi, Srivatsan Krishnan, Iou-Jen Liu, Cong Lu, Jincheng Mei, Chao Qin

Self-Supervised Learning - Theory and Practice
Invited Speakers include: Mathilde Caron

Symmetry and Geometry in Neural Representations (NeurReps)
Invited Speakers include: Noah Shutty
Program Committee includes: Ondrej Biza, Noah Shutty

Temporal Graph Learning Workshop
Invited Speakers include: Mehran Kazemi

Transfer Learning for Natural Language Processing
Workshop Organizers include: Deepak Ramachandran, Sebastian Ruder
Invited Speakers include: Jonas Pfeiffer
Invited Debaters include: Ellie Pavlick
Program Committee includes: Patrick Fernandes, Jonas Pfeiffer, Jiao Sun, Tu Vu, Xinyi Wang, Xin Xu

Cultures of AI and AI for Culture
Workshop Organizers include: Rida Qadri, Fernando Diaz

Deep Reinforcement Learning Workshop
Workshop Organizers include: Karol Hausman, Ted Xiao, Zeyu Zheng
Invited Speakers include: Igor Mordatch
Advisory Board includes: Chelsea Finn

Empowering Communities: A Participatory Approach to AI for Mental Health
Program Committee includes: Diana Mincu, Subhrajit Roy, Martin Seneviratne

HCAI@NeurIPS 2022, Human Centered AI
Keynote Speaker includes: Fernanda Viegas

Learning Meaningful Representations of Life
Workshop Organizers include: Adji Bousso Dieng

Machine Learning for Creativity and Design
Workshop Organizers include: Yingtao Tian

Machine Learning Safety
Workshop Organizers include: Nicholas Carlini
Invited Speakers include: Dorsa Sadigh

Neuro Causal and Symbolic AI (nCSI)
Workshop Organizers include: Thomas Kipf

Robot Learning Workshop: Trustworthy Robotics
Workshop Organizers include: Alex Bewley, Jonathan Tompson
Invited Speakers include: Karol Hausman, Brian Ichter, Been Kim, Leila Takayama, Andy Zeng
Program Committee includes: Vincent Vanhoucke

The Symbiosis of Deep Learning and Differential Equations II
Workshop Organizers include: Winnie Xu
Invited Speakers include: Rose Yu

Tackling Climate Change with Machine Learning
Workshop Organizers include: Emma Strubell

Trustworthy and Socially Responsible Machine Learning
Invited Speakers include: Been Kim, Dorsa Sadigh, Milind Tambe

Vision Transformers: Theory and Applications
Invited Speakers include: Cordelia Schmid, Ming Hsuan Yang


Advances in Bayesian Optimization
Tutorial Organizers include: Virginia Aglietti

Creative Culture and Machine Learning
Tutorial Organizers include: Negar Rostamzadeh

Fair and Socially Responsible ML for Recommendations: Challenges and Perspectives
Invited Panelists include: Fernando Diaz

Lifelong Learning Machines
Invited Panelists include: Christopher Summerfield

The Role of Meta-learning for Few-Shot Learning
Tutorial Organizers include: Eleni Triantafillou
Invited Panelists include: Neil Houlsby, Priyanka Agrawal


NeurIPS 2022 Competition Track: Overview & Results
Invited Speakers include: Isabelle Guyon

Causal Insights for Learning Paths in Education
Competition Organizers include: Zichao (Jack) Wang

IGLU: Interactive Grounded Language Understanding in a Collaborative Environment
Competition Organizers include: Negar Arabzadeh

Cross-Domain MetaDL: Any-Way Any-Shot Learning Competition with Novel Datasets from Practical Domains
Competition Organizers include: Isabelle Guyon

Reconnaissance Blind Chess: An Unsolved Challenge for Multi-Agent Decision Making Under Uncertainty
Competition Organizers include: Bo Li

VisDA 2022 Challenge: Sim2Real Domain Adaptation for Industrial Recycling
Competition Organizers include: Dina Bashkirova

Spotlight Papers

CoPur: Certifiably Robust Collaborative Inference via Feature Purification
Jing Liu, Chulin Xie, Oluwasanmi O Koyejo, Bo Li

Machine Learning on Graphs: A Model and Comprehensive Taxonomy
Ines Chami*, Sami Abu-El-Haija, Bryan Perozzi, Christopher Ré, Kevin Murphy

Sparse Winning Tickets are Data-Efficient Image Recognizers
Mukund Varma T, Xuxi Chen, Zhenyu Zhang, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang

Federated Learning from Pre-trained Models: A Contrastive Learning Approach
Yue Tan, Guodong Long, Jie Ma, Lu Liu, Tianyi Zhou, Jing Jiang

Improving Multi-task Generalization via Regularizing Spurious Correlation
Ziniu Hu*, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi

The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning
Yunhao Tang, Mark Rowland, Rémi Munos, Bernardo Ávila Pires, Will Dabney, Marc G. Bellemare

Residual Multiplicative Filter Networks for Multiscale Reconstruction
Shayan Shekarforoush, David B. Lindell, David J. Fleet, Marcus A Brubaker

Differentially Private Learning with Margin Guarantees
Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh

Optimal Query Complexities for Dynamic Trace Estimation
David P. Woodruff*, Fred Zhang*, Qiuyi Zhang


From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent
Ayush Sekhari, Satyen Kale, Jason D. Lee, Chris De Sa, Karthik Sridharan

On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games
Runyu Zhang, Jincheng Mei, Bo Dai, Dale Schuurmans, Na Li

Matryoshka Representation Learning
Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham Kakade, Prateek Jain, Ali Farhadi

Efficient Risk-Averse Reinforcement Learning
Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor

Operator Splitting Value Iteration
Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand

Cluster Randomized Designs for One-Sided Bipartite Experiments
Jennifer Brennan*, Vahab Mirrokni, Jean Pouget-Abadie

A Unified Sequence Interface for Vision Tasks
Ting Chen, Saurabh Saxena, Lala Li, Tsung-Yi Lin*, David J. Fleet, Geoffrey Hinton

Cryptographic Hardness of Learning Halfspaces with Massart Noise
Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi, Lisheng Ren

Better Best of Both Worlds Bounds for Bandits with Switching Costs
Idan Amir, Guy Azov, Tomer Koren, Roi Livni

Fast Neural Kernel Embeddings for General Activations
Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi

Hierarchical Agglomerative Graph Clustering in Poly-Logarithmic Depth
Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirronki, Jessica Shi

Improving Zero-Shot Generalization in Offline Reinforcement Learning Using Generalized Similarity Functions
Bogdan Mazoure*, Ilya Kostrikov, Ofir Nachum, Jonathan Tompson

Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples
Maura Pintor, Luca Demetrio, Angelo Sotgiu, Ambra Demontis, Nicholas Carlini, Battista Biggio, Fabio Roli

Learning Energy Networks with Generalized Fenchel-Young Losses
Mathieu Blondel, Felipe Llinares-López, Robert Dadashi, Léonard Hussenot, Matthieu Geist

Learning Robust Dynamics Through Variational Sparse Gating
Arnav Kumar Jain, Shiva Kanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner, Samira Ebrahimi Kahou

Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures
Arnav Kumar Jain, Shiva Kanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner, Samira Ebrahimi Kahou

So3krates: Equivariant Attention for Interactions on Arbitrary Length-Scales in Molecular Systems
J. Thorben Frank, Oliver T. Unke, Klaus-Robert Müller

Spectral Bias in Practice: The Role of Function Frequency in Generalization
Sara Fridovich-Keil*, Raphael Gontijo-Lopes, Rebecca Roelofs

Delving into Out-of-Distribution Detection with Vision-Language Representations
Yifei Ming, Ziyang Cai, Jiuxiang Gu, Yiyou Sun, Wei Li, Yixuan Li

Path Independent Equilibrium Models Can Better Exploit Test-Time Computation
Cem Anil, Ashwini Pokle, Kaiqu Liang, Johannes Treutlein, Yuhuai Wu, Shaojie Bai, J. Zico Kolter, Roger Grosse

On Optimal Learning Under Targeted Data Poisoning
Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran

Learning With Little Mixing
Ingvar Ziemann, Stephen Tu

Block-Recurrent Transformers
DeLesley Hutchins, Imanol Schlag*, Yuhuai Wu, Ethan Dyer, Behnam Neyshabur

TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets
Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc Le, Da Huang

Regret Bounds for Multilabel Classification in Sparse Label Regimes
Robert Busa-Fekete, Heejin Choi, Krzysztof Dembczynski, Claudio Gentile, Henry William Reeve, Balazs Szorenyi

Robust Reinforcement Learning Using Offline Data
Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh

Contrastive Learning as Goal-Conditioned Reinforcement Learning
Benjamin Eysenbach, Tianjun Zhang, Sergey Levine, Ruslan Salakhutdinov

Beyond Rewards: A Hierarchical Perspective on Offline Multiagent Behavioral Analysis
Shayegan Omidshafiei, Andrei Kapishnikov, Yannick Assogba, Lucas Dixon, Been Kim

Revisiting Neural Scaling Laws in Language and Vision
Ibrahim Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai

Polynomial Neural Fields for Subband Decomposition and Manipulation
Guandao Yang*, Sagie Benaim, Varun Jampani, Kyle Genova, Jonathan T. Barron, Thomas Funkhouser, Bharath Hariharan, Serge Belongie

First Is Better Than Last for Language Data Influence
Chih-Kuan Yeh, Ankur Taly, Mukund Sundararajan, Frederick Liu, Pradeep Ravikumar

The Privacy Onion Effect: Memorization Is Relative
Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramer

Deep Hierarchical Planning from Pixels (see blog post)
Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel

Discovered Policy Optimisation
Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schroeder de Witt, Jakob Foerster

Semi-supervised Active Linear Regression
Fnu Devvrit, Nived Rajaraman, Pranjal Awasthi

Pruning’s Effect on Generalization Through the Lens of Training and Regularization
Tian Jin, Daniel M. Roy, Michael Carbin, Jonathan Frankle, Gintare Karolina Dziugaite

Exploring Length Generalization in Large Language Models
Cem Anil*, Yuhuai Wu, Anders Andreassen, Aitor Lewkowycz, Vedant Misra, Vinay Ramasesh, Ambrose Slone, Guy Gur-Ari, Ethan Dyer, Behnam Neyshabur

Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm Under Parallelization
Benjamin Dubois-Taine, Francis Bach, Quentin Berthet, Adrien Taylor

Global Normalization for Streaming Speech Recognition in a Modular Framework
Ehsan Variani, Ke Wu, Michael Riley, David Rybach, Matt Shannon, Cyril Allauzen

Learning Predictions for Algorithms with Predictions
Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar, Sergei Vassilvitskii

Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts (see blog post)
Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby

Incrementality Bidding via Reinforcement Learning Under Mixed and Delayed Rewards
Ashwinkumar Badanidiyuru, Zhe Feng, Tianxi Li, Haifeng Xu*

Solving Quantitative Reasoning Problems with Language Models (see blog post)
Aitor Lewkowycz, Anders Andreassen, David Dohan, Ethan Dyer, Henryk Michalewski, Vinay Ramasesh, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur, Guy Gur-Ari, Vedant Misra

Anonymized Histograms in Intermediate Privacy Models
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

Efficient and Stable Fully Dynamic Facility Location
Sayan Bhattacharya, Nikos Parotsidis, Silvio Lattanzi

Are All Losses Created Equal: A Neural Collapse Perspective
Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu

Universal Rates for Interactive Learning
Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas

Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions
Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu

Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes
Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning
Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang

Pre-trained Language Models for Interactive Decision-Making
Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu

Polynomial Neural Fields for Subband Decomposition and Manipulation
Guandao Yang*, Sagie Benaim, Varun Jampani, Kyle Genova, Jonathan T. Barron, Thomas Funkhouser, Bharath Hariharan, Serge Belongie

Submodular Maximization in Clean Linear Time
Wenxin Li, Moran Feldman, Ehsan Kazemi, Amin Karbasi

Reinforcement Learning with Logarithmic Regret and Policy Switches
Grigoris Velegkas, Zhuoran Yang, Amin Karbasi

Algorithms with Prediction Portfolios
Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii

Understanding and Improving Robustness of Vision Transformers Through Patch-Based Negative Augmentation
Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang

Best of Both Worlds Model Selection
Aldo Pacchiano, Christoph Dann, Claudio Gentile

Fair Wrapping for Black-Box Predictions
Alexander Soen, Ibrahim Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie

A Reduction to Binary Approach for Debiasing Multiclass Datasets
Ibrahim Alabdulmohsin, Jessica Schrouff, Oluwasanmi Koyejo

Weighted Distillation with Unlabeled Examples
Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trihn,Erik Vee

A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases
James Harrison, Luke Metz, Jascha Sohl-Dickstein

Post-hoc Estimators for Learning to Defer to an Expert
Harikrishna Narasimhan, Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar

Model-Based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity
Alekh Agarwal, Tong Zhang

On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL
Jinglin Chen, Aditya Modi, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal

Towards Learning Universal Hyperparameter Optimizers with Transformers (see blog post)
Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Qiuyi Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'aurelio Ranzato, Sagi Perel, Nando de Freitas

Reproducibility in Optimization: Theoretical Framework and Limits
Kwangjun Ahn*, Prateek Jain, Ziwei Ji, Satyen Kale, Praneeth Netrapalli, Gil I. Shamir

Confident Adaptive Language Modeling
Tal Schuster, Adam Fisch, Jai Gupta, Mostafa Dehghani, Dara Bahri, Vinh Q. Tran, Yi Tay, Donald Metzler

Reinforcement Learning with Neural Radiance Fields
Danny Driess, Ingmar Schubert, Pete Florence, Yunzhu Li, Marc Toussaint

Invariant and Transportable Representations for Anti-Causal Domain Shifts
Yibo Jiang, Victor Veitch

Simple Mechanisms for Welfare Maximization in Rich Advertising Auctions
Gagan Aggarwal, Kshipra Bhawalkar, Aranyak Mehta, Divyarthi Mohan, Alexandros Psomas

STaR: Bootstrapping Reasoning with Reasoning
Eric Zelikman, Yuhuai Wu, Jesse Mu, Noah D. Goodman

Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality
Teodor V. Marinov, Mehryar Mohri, Julian Zimmert

The Curse of Unrolling: Rate of Differentiating Through Optimization
Damien Scieur, Quentin Bertrand, Gauthier Gidel, Fabian Pedregosa

Visual Prompting via Image Inpainting
Amir Bar, Yossi Gandelsman, Trevor Darrell, Amir Globerson, Alexei A Efros

Multi-Class H-Consistency Bounds
Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

Anonymous Bandits for Multi-User Systems
Hossein Esfandiari, Vahab Mirrokni, Jon Schneider

Understanding the Eluder Dimension
Gene Li, Pritish Kamath, Dylan J. Foster, Nathan Srebro

Why So Pessimistic? Estimating Uncertainties for Offline RL Through Ensembles, and Why Their Independence Matters
Seyed Kamyar Seyed Ghasemipour, Shixiang Shane Gu, Ofir Nachum

A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback
Saeed Masoudian, Julian Zimmert, Yevgeny Seldin

A Theoretical View on Sparsely Activated Networks
Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang

Chain of Thought Prompting Elicits Reasoning in Large Language Models (see blog post)
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, Denny Zhou

Decoupled Context Processing for Context Augmented Language Modeling
Zonglin Li, Ruiqi Guo, Sanjiv Kumar

Exploring Through Random Curiosity with General Value Functions
Aditya Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber

Object Scene Representation Transformer
Mehdi S. M. Sajjadi, Daniel Duckworth, Aravindh Mahendran, Sjoerd van Steenkiste, Filip Pavetić, Mario Lučić, Leonidas J. Guibas, Klaus Greff, Thomas Kipf

Joint Model-Policy Optimization of a Lower Bound for Model-Based RL
Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov

A Fourier Approach to Mixture Learning
Mingda Qiao*, Guru Guruganesh, Ankit Singh Rawat, Avinava Dubey, Manzil Zaheer

Why Neural Networks Find Simple Solutions: The Many Regularizers of Geometric Complexity
Benoit Dherin, Michael Munn, Mihaela Rosca, David Barrett

Do Current Multi-task Optimization Methods in Deep Learning Even Help?
Derrick Xin, Behrooz Ghorbani, Ankush Garg, Orhan Firat, Justin Gilmer

Associating Objects and Their Effects in Video Through Coordination Games
Erika Lu, Forrester Cole, Weidi Xie, Tali Dekel, William Freeman, Andrew Zisserman, Michael Rubinstein

Increasing Confidence in Adversarial Robustness Evaluations
Roland S. Zimmermann*, Wieland Brendel, Florian Tramèr, Nicholas Carlini

The Role of Baselines in Policy Gradient Optimization
Jincheng Mei, Wesley Chung, Valentin Thomas, Bo Dai, Csaba Szepesvari, Dale Schuurmans

Scaling Multimodal Pre-training via Cross-Modality Gradient Harmonization
Junru Wu, Yi Liang, Feng Han, Hassan Akbari, Zhangyang Wang, Cong Yu*

S3GC: Scalable Self-Supervised Graph Clustering
Fnu Devvrit*, Aditya Sinha, Inderjit Dhillon, Prateek Jain

Algorithms and Hardness for Learning Linear Thresholds from Label Proportions
Rishi Saket

ALMA: Hierarchical Learning for Composite Multi-Agent Tasks
Shariq Iqbal, Robby Costales, Fei Sha

DC-BENCH: Dataset Condensation Benchmark
Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh

Does GNN Pre-training Help Molecular Representation?
Ruoxi Sun, Hanjun Dai, Adams Yu

Drawing Out of Distribution with Neuro-Symbolic Generative Models
Yichao Liang, Joshua B. Tenenbaum, Tuan Anh Le, N. Siddharth

Mixture-of-Experts with Expert Choice Routing (see blog post)
Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Zhao, Andrew Dai, Zhifeng Chen, Quoc Le, James Laudon

Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback
Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg

Precise Learning Curves and Higher-Order Scalings for Dot-Product Kernel Regression
Lechao Xiao, Jeffrey Pennington, Theodor Misiakiewicz, Hong Hu, Yue Lu

Rate-Optimal Online Convex Optimization in Adaptive Linear Control
Asaf Cassel, Alon Cohen, Tomer Koren

Why Neural Networks Find Simple Solutions: The Many Regularizers of Geometric Complexity
Benoit Dherin, Michael Munn, Mihaela Rosca, David G.T. Barrett

Private Isotonic Regression
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

Sketching Based Representations for Robust Image Classification with Provable Guarantees
Nishanth Dikkala, Sankeerth Rao Karingula, Raghu Meka, Jelani Nelson, Rina Panigrahy, Xin Wang

The Role of Baselines in Policy Gradient Optimization
Jincheng Mei, Wesley Chung, Valentin Thomas, Bo Dai, Csaba Szepesvari, Dale Schuurmans

Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens
Elad Ben Avraham, Roei Herzig, Karttikeya Mangalam, Amir Bar, Anna Rohrbach, Leonid Karlinsky, Trevor Darrell, Amir Globerson

Near-Optimal Private and Scalable k-Clustering
Vincent Cohen-Addad, Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan*, Peilin Zhong

When Does Differentially Private Learning Not Suffer in High Dimensions?
Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin A Inan, Janardhan Kulkarni, YinTat Lee, Abhradeep Guha Thakurta

End-to-End Learning to Index and Search in Large Output Spaces
Nilesh Gupta, Patrick H. Chen, Hsiang-Fu, Yu, Cho-Jui Hsieh, Inderjit S. Dhillon

A Boosting Approach to Reinforcement Learning
Nataly Brukhim, Elad Hazan, Karan Singh

FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction
Samiul Alam, Luyang Liu, Ming Yan, Mi Zhang

Non-Convex Online Learning via Algorithmic Equivalence
Udaya Ghai, Zhou Lu, Elad Hazan

Is this the Right Neighborhood? Accurate and Query Efficient Model Agnostic Explanations
Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Karthikeyan Shanmugam

SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videos
Gamaleldin F. Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael C. Mozer, Thomas Kipf

UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes
Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby

Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions
Courtney Paquette, Elliot Paquette, Ben Adlam, Jeffrey Pennington

Multi-game Decision Transformers (see blog post)
Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Winnie Xu, Sergio Guadarrama, Ian Fischer, Eric Jang, Henryk Michalewski, Igor Mordatch

Subsidiary Prototype Alignment for Universal Domain Adaptation
Jogendra Nath Kundu, Suvaansh Bhambri, Akshay Ravindra Kulkarni, Hiran Sarkar, Varun Jampani, Venkatesh Babu Radhakrishnan

SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections
Mark Boss*, Andreas Engelhardt*, Abhishek Kar, Yuanzhen Li, Deqing Sun, Jonathan T. Barron, Hendrik P. A. Lensch, Varun Jampani

Chefs’ Random Tables: Non-Trigonometric Random Features
Valerii Likhosherstov, Krzysztof Marcin Choromanski, Avinava Dubey, Frederick Liu, Tamas Sarlos, Adrian Weller

Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks
Mansheej Paul, Brett W Larsen, Surya Ganguli, Jonathan Frankle, Gintare Karolina Dziugaite

DP-PCA: Statistically Optimal and Differentially Private PCA
Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh

Emergent Communication: Generalization and Overfitting in Lewis Games
Mathieu Rita, Corentin Tallec, Paul Michel, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux, Florian Strub

Handcrafted Backdoors in Deep Neural Networks
Sanghyun Hong, Nicholas Carlini, Alexey Kurakin

I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification
Muhammad Ferjad Naeem, Yongqin Xian, Luc Van Gool, Federico Tombari

Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams
Sergey Denisov, Brendan McMahan, Keith Rush, Adam Smith, Abhradeep Guha Thakurta

Optimal Scaling for Locally Balanced Proposals in Discrete Spaces
Haoran Sun*, Hanjun Dai, Dale Schuurmans

Near-Optimal Correlation Clustering with Privacy
Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi, Slobodan Mitrović, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski

Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers
Albert Q. Jiang, Wenda Li, Szymon Tworkowski, Konrad Czechowski, Tomasz Odrzygóźdź, Piotr Miłoś, Yuhuai Wu, Mateja Jamnik

TPU-KNN: K Nearest Neighbor Search at Peak FLOP/s
Felix Chern, Blake Hechtman, Andy Davis, Ruiqi Guo, David Majnemer, Sanjiv Kumar

When Does Dough Become a Bagel? Analyzing the Remaining Mistakes on ImageNet
Vijay Vasudevan, Benjamin Caine, Raphael Gontijo-Lopes, Sara Fridovich-Keil, Rebecca Roelofs

DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning
Quan Vuong, Aviral Kumar, Sergey Levine, Yevgen Chebotar

A Characterization of Semi-Supervised Adversarially Robust PAC Learnability
Idan Attias, Steve Hanneke, Yishay Mansour

Back Razor: Memory-Efficient Transfer Learning by Self-Sparsified Backpropagation
Ziyu Jiang, Xuxi Chen, Xueqin Huang, Xianzhi Du, Denny Zhou, Zhangyang Wang

Subquadratic Kronecker Regression with Applications to Tensor Decomposition
Matthew Fahrbach, Gang Fu, Mehrdad Ghadiri

Zero-Shot Transfer Learning Within a Heterogeneous Graph via Knowledge Transfer Networks
Minji Yoon*, John Palowitch, Dustin Zelle, Ziniu Hu*, Ruslan Salakhutdinov, Bryan Perozzi

Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank
Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong

Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress (see blog post)
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron Courville, Marc G. Bellemare

Private and Communication-Efficient Algorithms for Entropy Estimation
Gecia Bravo-Hermsdorff, Robert Busa-Fekete, Mohammad Ghavamzadeh, Andres Munoz Medina, Umar Syed

Oracle Inequalities for Model Selection in Offline Reinforcement Learning
Jonathan Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill

Diagnosing Failures of Fairness Transfer Across Distribution Shift in Real-World Medical Settings
Jessica Schrouff*, Natalie Harris, Oluwasanmi O Koyejo, Ibrahim Alabdulmohsin, Eva Schnider*, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A Heller, Silvia Chiappa, Alexander D'Amour

LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discovery
Chun-Han Yao, Wei-Chih Hung, Yuanzhen Li, Michael Rubinstein, Ming-Hsuan Yang, Varun Jampani

Patching Open-Vocabulary Models by Interpolating Weights
Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song, Hannaneh Hajishirzi, Simon Kornblith, Ali Farhadi, Ludwig Schmidt

TUSK: Task-Agnostic Unsupervised Keypoints
Yuhe Jin, Weiwei Sun, Jan Hosang, Eduard Trulls, Kwang Moo Yi

Active Learning of Classifiers with Label and Seed Queries
Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice, Maximilian Thiessen

Autoformalization with Large Language Models
Yuhuai Wu, Albert Q. Jiang, Wenda Li, Markus N. Rabe, Charles Staats, Mateja Jamnik, Christian Szegedy

Benign Underfitting of Stochastic Gradient Descent
Tomer Koren, Roi Livni, Yishay Mansour, Uri Sherman

Chain of Thought Imitation with Procedure Cloning
Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum

Efficient and Modular Implicit Differentiation
Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert

Insights into Pre-training via Simpler Synthetic Tasks
Yuhuai Wu, Felix Li, Percy Liang

Self-Supervised Learning with an Information Maximization Criterion
Serdar Ozsoy, Shadi Hamdan, Sercan Ö. Arik, Deniz Yuret, Alper T. Erdogan

Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model
Weihao Kong, Rajat Sen, Pranjal Awasthi, Abhimanyu Das

Using Embeddings for Causal Estimation of Peer Influence in Social Networks
Irina Cristali, Victor Veitch

VCT: A Video Compression Transformer
Fabian Mentzer, George Toderici, David Minnen, Sung-Jin Hwang, Sergi Caelles, Mario Lucic, Eirikur Agustsson

Video Diffusion Models
Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet

Large Language Models are Zero-Shot Reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, Yusuke Iwasawa

Improved Coresets for Euclidean k-Means
Vincent Cohen-Addad, Kasper Green Larsen, David Saulpic, Chris Schwiegelshohn, Omar Ali Sheikh-Omar

On the Adversarial Robustness of Mixture of Experts
Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme Ruiz, Pranjal Awasthi, Srinadh Bhojanapalli

Stars: Tera-Scale Graph Building for Clustering and Learning
CJ Carey, Jonathan Halcrow, Rajesh Jayaram, Vahab Mirrokni, Warren Schudy, Peilin Zhong

VER: Scaling On-Policy RL Leads to the Emergence of Navigation in Embodied Rearrangement
Erik Wijmans, Irfan Essa, Dhruv Batra

TaSIL: Taylor Series Imitation Learning
Daniel Pfrommer, Thomas TCK Zhang, Stephen Tu, Nikolai Matni

RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks
Leo Kozachkov, Michaela M Ennis, Jean-Jacques Slotine

Integral Probability Metrics PAC-Bayes Bounds
Ron Amit, Baruch Epstein, Shay Moran, Ron Meir

D2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video
Tianhao Wu, Fangcheng Zhong, Andrea Tagliasacchi, Forrester Cole, Cengiz Oztireli

Posted Pricing and Dynamic Prior-Independent Mechanisms with Value Maximizers
Yuan Deng, Vahab Mirrokni, Hanrui Zhang

Transformer Memory as a Differentiable Search Index
Yi Tay, Vinh Q. Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Gupta, Tal Schuster, William W. Cohen, Donald Metzler

*Work done while at Google.  

Source: Google AI Blog

Google at ECCV 2022

Google is proud to be a Platinum Sponsor of the European Conference on Computer Vision (ECCV 2022), a premier forum for the dissemination of research in computer vision and machine learning (ML). This year, ECCV 2022 will be held as a hybrid event, in person in Tel Aviv, Israel with virtual attendance as an option. Google has a strong presence at this year’s conference with over 60 accepted publications and active involvement in a number of workshops and tutorials. We look forward to sharing some of our extensive research and expanding our partnership with the broader ML research community.

Registered for ECCV 2022? We hope you’ll visit our on-site or virtual booths to learn more about the research we’re presenting at ECCV 2022, including several demos and opportunities to connect with our researchers. Learn more about Google's research being presented at ECCV 2022 below (Google affiliations in bold).

Organizing Committee

Program Chairs include: Moustapha Cissé

Awards Paper Committee: Todd Zickler

Area Chairs include: Ayan Chakrabarti, Tali Dekel, Alireza Fathi, Vittorio Ferrari, David Fleet, Dilip Krishnan, Michael Rubinstein, Cordelia Schmid, Deqing Sun, Federico Tombari, Jasper Uijlings, Ming-Hsuan Yang, Todd Zickler

Accepted Publications

NeuMesh: Learning Disentangled Neural Mesh-Based Implicit Field for Geometry and Texture Editing
Bangbang Yang, Chong Bao, Junyi Zeng, Hujun Bao, Yinda Zhang, Zhaopeng Cui, Guofeng Zhang

Anti-Neuron Watermarking: Protecting Personal Data Against Unauthorized Neural Networks
Zihang Zou, Boqing Gong, Liqiang Wang

Exploiting Unlabeled Data with Vision and Language Models for Object Detection
Shiyu Zhao, Zhixing Zhang, Samuel Schulter, Long Zhao, Vijay Kumar B G, Anastasis Stathopoulos, Manmohan Chandraker, Dimitris N. Metaxas

Waymo Open Dataset: Panoramic Video Panoptic Segmentation
Jieru Mei, Alex Zhu, Xinchen Yan, Hang Yan, Siyuan Qiao, Yukun Zhu, Liang-Chieh Chen, Henrik Kretzschmar

PRIF: Primary Ray-Based Implicit Function
Brandon Yushan Feng, Yinda Zhang, Danhang Tang, Ruofei Du, Amitabh Varshney

LoRD: Local 4D Implicit Representation for High-Fidelity Dynamic Human Modeling
Boyan Jiang, Xinlin Ren, Mingsong Dou, Xiangyang Xue, Yanwei Fu, Yinda Zhang

k-Means Mask Transformer (see blog post)
Qihang Yu*, Siyuan Qiao, Maxwell D Collins, Yukun Zhu, Hartwig Adam, Alan Yuille, Liang-Chieh Chen

MaxViT: Multi-Axis Vision Transformer (see blog post)
Zhengzhong Tu, Hossein Talebi, Han Zhang, Feng Yang, Peyman Milanfar, Alan Bovik, Yinxiao Li

E-Graph: Minimal Solution for Rigid Rotation with Extensibility Graphs
Yanyan Li, Federico Tombari

RBP-Pose: Residual Bounding Box Projection for Category-Level Pose Estimation
Ruida Zhang, Yan Di, Zhiqiang Lou, Fabian Manhardt, Federico Tombari, Xiangyang Ji

GOCA: Guided Online Cluster Assignment for Self-Supervised Video Representation Learning
Huseyin Coskun, Alireza Zareian, Joshua L Moore, Federico Tombari, Chen Wang

Scaling Open-Vocabulary Image Segmentation with Image-Level Labels
Golnaz Ghiasi, Xiuye Gu, Yin Cui, Tsung-Yi Lin*

Adaptive Transformers for Robust Few-Shot Cross-Domain Face Anti-spoofing
Hsin-Ping Huang, Deqing Sun, Yaojie Liu, Wen-Sheng Chu, Taihong Xiao, Jinwei Yuan, Hartwig Adam, Ming-Hsuan Yang

DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning
Zifeng Wang*, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, Tomas Pfister

BLT: Bidirectional Layout Transformer for Controllable Layout Generation
Xiang Kong, Lu Jiang, Huiwen Chang, Han Zhang, Yuan Hao, Haifeng Gong, Irfan Essa

V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer
Runsheng Xu, Hao Xiang, Zhengzhong Tu, Xin Xia, Ming-Hsuan Yang, Jiaqi Ma

Learning Visibility for Robust Dense Human Body Estimation
Chun-Han Yao, Jimei Yang, Duygu Ceylan, Yi Zhou, Yang Zhou, Ming-Hsuan Yang

Are Vision Transformers Robust to Patch Perturbations?
Jindong Gu, Volker Tresp, Yao Qin

PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds
Zhaoqi Leng, Shuyang Cheng, Ben Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov

Structure and Motion from Casual Videos
Zhoutong Zhang, Forrester Cole, Zhengqi Li, Noah Snavely, Michael Rubinstein, William T. Freeman

PreTraM: Self-Supervised Pre-training via Connecting Trajectory and Map
Chenfeng Xu, Tian Li, Chen Tang, Lingfeng Sun, Kurt Keutzer, Masayoshi Tomizuka, Alireza Fathi, Wei Zhan

Novel Class Discovery Without Forgetting
Joseph K J, Sujoy Paul, Gaurav Aggarwal, Soma Biswas, Piyush Rai, Kai Han, Vineeth N Balasubramanian

Hierarchically Self-Supervised Transformer for Human Skeleton Representation Learning
Yuxiao Chen, Long Zhao, Jianbo Yuan, Yu Tian, Zhaoyang Xia, Shijie Geng, Ligong Han, Dimitris N. Metaxas

PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks
Nan Ding, Xi Chen, Tomer Levinboim, Soravit Changpinyo, Radu Soricut

InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images
Zhengqi Li, Qianqian Wang*, Noah Snavely, Angjoo Kanazawa*

Generalizable Patch-Based Neural Rendering (see blog post)
Mohammed Suhail*, Carlos Esteves, Leonid Sigal, Ameesh Makadia

LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds
Minghua Liu, Yin Zhou, Charles R. Qi, Boqing Gong, Hao Su, Dragomir Anguelov

The Missing Link: Finding Label Relations Across Datasets
Jasper Uijlings, Thomas Mensink, Vittorio Ferrari

Learning Instance-Specific Adaptation for Cross-Domain Segmentation
Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang

Learning Audio-Video Modalities from Image Captions
Arsha Nagrani, Paul Hongsuck Seo, Bryan Seybold, Anja Hauth, Santiago Manen, Chen Sun, Cordelia Schmid

TL;DW? Summarizing Instructional Videos with Task Relevance & Cross-Modal Saliency
Medhini Narasimhan*, Arsha Nagrani, Chen Sun, Michael Rubinstein, Trevor Darrell, Anna Rohrbach, Cordelia Schmid

On Label Granularity and Object Localization
Elijah Cole, Kimberly Wilber, Grant Van Horn, Xuan Yang, Marco Fornoni, Pietro Perona, Serge Belongie, Andrew Howard, Oisin Mac Aodha

Disentangling Architecture and Training for Optical Flow
Deqing Sun, Charles Herrmann, Fitsum Reda, Michael Rubinstein, David J. Fleet, William T. Freeman

NewsStories: Illustrating Articles with Visual Summaries
Reuben Tan, Bryan Plummer, Kate Saenko, J.P. Lewis, Avneesh Sud, Thomas Leung

Improving GANs for Long-Tailed Data Through Group Spectral Regularization
Harsh Rangwani, Naman Jaswani, Tejan Karmali, Varun Jampani, Venkatesh Babu Radhakrishnan

Planes vs. Chairs: Category-Guided 3D Shape Learning Without Any 3D Cues
Zixuan Huang, Stefan Stojanov, Anh Thai, Varun Jampani, James Rehg

A Sketch Is Worth a Thousand Words: Image Retrieval with Text and Sketch
Patsorn Sangkloy, Wittawat Jitkrittum, Diyi Yang, James Hays

Learned Monocular Depth Priors in Visual-Inertial Initialization
Yunwen Zhou, Abhishek Kar, Eric L. Turner, Adarsh Kowdle, Chao Guo, Ryan DuToit, Konstantine Tsotsos

How Stable are Transferability Metrics Evaluations?
Andrea Agostinelli, Michal Pandy, Jasper Uijlings, Thomas Mensink, Vittorio Ferrari

Data-Free Neural Architecture Search via Recursive Label Calibration
Zechun Liu*, Zhiqiang Shen, Yun Long, Eric Xing, Kwang-Ting Cheng, Chas H. Leichner

Fast and High Quality Image Denoising via Malleable Convolution
Yifan Jiang*, Bartlomiej Wronski, Ben Mildenhall, Jonathan T. Barron, Zhangyang Wang, Tianfan Xue

Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation
Jogendra Nath Kundu, Suvaansh Bhambri, Akshay R Kulkarni, Hiran Sarkar,
Varun Jampani, Venkatesh Babu Radhakrishnan

Learning Online Multi-Sensor Depth Fusion
Erik Sandström, Martin R. Oswald, Suryansh Kumar, Silvan Weder, Fisher Yu, Cristian Sminchisescu, Luc Van Gool

Hierarchical Semantic Regularization of Latent Spaces in StyleGANs
Tejan Karmali, Rishubh Parihar, Susmit Agrawal, Harsh Rangwani, Varun Jampani, Maneesh K Singh, Venkatesh Babu Radhakrishnan

RayTran: 3D Pose Estimation and Shape Reconstruction of Multiple Objects from Videos with Ray-Traced Transformers
Michał J Tyszkiewicz, Kevis-Kokitsi Maninis, Stefan Popov, Vittorio Ferrari

Neural Video Compression Using GANs for Detail Synthesis and Propagation
Fabian Mentzer, Eirikur Agustsson, Johannes Ballé, David Minnen, Nick Johnston, George Toderici

Exploring Fine-Grained Audiovisual Categorization with the SSW60 Dataset
Grant Van Horn, Rui Qian, Kimberly Wilber, Hartwig Adam, Oisin Mac Aodha, Serge Belongie

Implicit Neural Representations for Image Compression
Yannick Strümpler, Janis Postels, Ren Yang, Luc Van Gool, Federico Tombari

3D Compositional Zero-Shot Learning with DeCompositional Consensus
Muhammad Ferjad Naeem, Evin Pınar Örnek, Yongqin Xian, Luc Van Gool, Federico Tombari

FindIt: Generalized Localization with Natural Language Queries (see blog post)
Weicheng Kuo, Fred Bertsch, Wei Li, AJ Piergiovanni, Mohammad Saffar, Anelia Angelova

A Simple Single-Scale Vision Transformer for Object Detection and Instance Segmentation
Wuyang Chen*, Xianzhi Du, Fan Yang, Lucas Beyer, Xiaohua Zhai, Tsung-Yi Lin, Huizhong Chen, Jing Li, Xiaodan Song, Zhangyang Wang, Denny Zhou

Improved Masked Image Generation with Token-Critic
Jose Lezama, Huiwen Chang, Lu Jiang, Irfan Essa

Learning Discriminative Shrinkage Deep Networks for Image Deconvolution
Pin-Hung Kuo, Jinshan Pan, Shao-Yi Chien, Ming-Hsuan Yang

AudioScopeV2: Audio-Visual Attention Architectures for Calibrated Open-Domain On-Screen Sound Separation
Efthymios Tzinis*, Scott Wisdom, Tal Remez, John Hershey

Simple Open-Vocabulary Object Detection with Vision Transformers
Matthias Minderer, Alexey Gritsenko, Austin C Stone, Maxim Neumann, Dirk Weißenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, Neil Houlsby

COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only Modality
Honglu Zhou, Asim Kadav, Aviv Shamsian, Shijie Geng, Farley Lai, Long Zhao, Ting Liu, Mubbasir Kapadia, Hans Peter Graf

Video Question Answering with Iterative Video-Text Co-tokenization (see blog post)
AJ Piergiovanni, Kairo Morton*, Weicheng Kuo, Michael S. Ryoo, Anelia Angelova

Class-Agnostic Object Detection with Multi-modal Transformer
Muhammad Maaz, Hanoona Abdul Rasheed, Salman Khan, Fahad Shahbaz Khan, Rao Muhammad Anwer, Ming-Hsuan Yang

FILM: Frame Interpolation for Large Motion (see blog post)
Fitsum Reda, Janne Kontkanen, Eric Tabellion, Deqing Sun, Caroline Pantofaru, Brian Curless

Compositional Human-Scene Interaction Synthesis with Semantic Control
Kaifeng Zhao, Shaofei Wang, Yan Zhang, Thabo Beeler, Siyu Tang


LatinX in AI
Mentors include: José Lezama
Keynote Speakers include: Andre Araujo

AI for Creative Video Editing and Understanding
Keynote Speakers include: Tali Dekel, Negar Rostamzadeh

Learning With Limited and Imperfect Data (L2ID)
Invited Speakers include: Xiuye Gu
Organizing Committee includes: Sadeep Jayasumana

International Challenge on Compositional and Multimodal Perception (CAMP)
Program Committee includes: Edward Vendrow

Self-Supervised Learning: What is Next?
Invited Speakers include: Mathilde Caron, Arsha Nagrani
Organizers include: Andrew Zisserman

3rd Workshop on Adversarial Robustness In the Real World
Invited Speakers include: Ekin Dogus Cubuk
Organizers include: Xinyun Chen, Alexander Robey, Nataniel Ruiz, Yutong Bai

AV4D: Visual Learning of Sounds in Spaces
Invited Speakers include: John Hershey

Challenge on Mobile Intelligent Photography and Imaging (MIPI)
Invited Speakers include: Peyman Milanfar

Robust Vision Challenge 2022
Organizing Committee includes: Alina Kuznetsova

Computer Vision in the Wild
Challenge Organizers include: Yi-Ting Chen, Ye Xia
Invited Speakers include: Yin Cui, Yongqin Xian, Neil Houlsby

Self-Supervised Learning for Next-Generation Industry-Level Autonomous Driving (SSLAD)
Organizers include: Fisher Yu

Responsible Computer Vision
Organizing Committee includes: Been Kim
Invited Speakers include: Emily Denton

Cross-Modal Human-Robot Interaction
Invited Speakers include: Peter Anderson

ISIC Skin Image Analysis
Organizing Committee includes: Yuan Liu
Steering Committee includes: Yuan Liu, Dale Webster
Invited Speakers include: Yuan Liu

Observing and Understanding Hands in Action
Sponsored by Google

Autonomous Vehicle Vision (AVVision)
Speakers include: Fisher Yu

Visual Perception for Navigation in Human Environments: The JackRabbot Human Body Pose Dataset and Benchmark
Organizers include: Edward Vendrow

Language for 3D Scenes
Invited Speakers include: Jason Baldridge
Organizers include: Leonidas Guibas

Designing and Evaluating Computer Perception Systems (CoPe)
Organizers include: Andrew Zisserman

Learning To Generate 3D Shapes and Scenes
Panelists include: Pete Florence

Advances in Image Manipulation
Program Committee includes: George Toderici, Ming-Hsuan Yang

TiE: Text in Everything
Challenge Organizers include: Shangbang Long, Siyang Qin
Invited Speakers include: Tali Dekel, Aishwarya Agrawal

Instance-Level Recognition
Organizing Committee: Andre Araujo, Bingyi Cao, Tobias Weyand
Invited Speakers include: Mathilde Caron

What Is Motion For?
Organizing Committee: Deqing Sun, Fitsum Reda, Charles Herrmann
Invited Speakers include: Tali Dekel

Neural Geometry and Rendering: Advances and the Common Objects in 3D Challenge
Invited Speakers include: Ben Mildenhall

Visual Object-Oriented Learning Meets Interaction: Discovery, Representations, and Applications
Invited Speakers include: Klaus Greff, Thomas Kipf
Organizing Committee includes: Leonidas Guibas

Vision with Biased or Scarce Data (VBSD)
Program Committee includes: Yizhou Wang

Multiple Object Tracking and Segmentation in Complex Environments
Invited Speakers include: Xingyi Zhou, Fisher Yu

3rd Visual Inductive Priors for Data-Efficient Deep Learning Workshop
Organizing Committee includes: Ekin Dogus Cubuk

DeeperAction: Detailed Video Action Understanding and Anomaly Recognition
Advisors include: Rahul Sukthankar

Sign Language Understanding Workshop and Sign Language Recognition, Translation & Production Challenge
Organizing Committee includes: Andrew Zisserman
Speakers include: Andrew Zisserman

Ego4D: First-Person Multi-Modal Video Understanding
Invited Speakers include: Michal Irani

AI-Enabled Medical Image Analysis: Digital Pathology & Radiology/COVID19
Program Chairs include: Po-Hsuan Cameron Chen
Workshop Partner: Google Health

Visual Object Tracking Challenge (VOT 2022)
Technical Committee includes: Christoph Mayer

Assistive Computer Vision and Robotics
Technical Committee includes: Maja Mataric

Human Body, Hands, and Activities from Egocentric and Multi-View Cameras
Organizers include: Francis Engelmann

Frontiers of Monocular 3D Perception: Implicit x Explicit
Panelists include: Pete Florence


Self-Supervised Representation Learning in Computer Vision
Invited Speakers include: Ting Chen

Neural Volumetric Rendering for Computer Vision
Organizers include: Ben Mildenhall, Pratul Srinivasan, Jon Barron
Presenters include: Ben Mildenhall, Pratul Srinivasan

New Frontiers in Efficient Neural Architecture Search!
Speakers include: Ruochen Wang

*Work done while at Google.  

Source: Google AI Blog