Co-Reyes, John D.

14 publications

ICLR 2025 Training Language Models to Self-Correct via Reinforcement Learning Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal Behbahani, Aleksandra Faust

TMLR 2024 Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models Avi Singh, John D Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron T Parisi, Abhishek Kumar, Alexander A Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin Fathy Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura A Culp, Lechao Xiao, Maxwell Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel

ICLRW 2024 Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models Avi Singh, John D Co-Reyes, Rishabh Agarwal

NeurIPS 2024 Many-Shot In-Context Learning Rishabh Agarwal, Avi Singh, Lei Zhang, Bernd Bohnet, Luis Rosias, Stephanie Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal Behbahani, Aleksandra Faust, Hugo Larochelle

ICMLW 2024 Many-Shot In-Context Learning Rishabh Agarwal, Avi Singh, Lei M Zhang, Bernd Bohnet, Luis Rosias, Stephanie C.Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D Co-Reyes, Eric Chu, Feryal Behbahani, Aleksandra Faust, Hugo Larochelle

ICLR 2024 Small-Scale Proxies for Large-Scale Transformer Training Instabilities Mitchell Wortsman, Peter J Liu, Lechao Xiao, Katie E Everett, Alexander A Alemi, Ben Adlam, John D Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith

ICMLW 2023 Guided Evolution with Binary Predictors for ML Program Search John D Co-Reyes, Yingjie Miao, George Tucker, Aleksandra Faust, Esteban Real

AutoML 2022 Differentiable Architecture Search for Reinforcement Learning Yingjie Miao, Xingyou Song, John D Co-Reyes, Daiyi Peng, Summer Yue, Eugene Brevdo, Aleksandra Faust

ICLRW 2022 Multi-Objective Evolution for Generalizable Policy Gradient Algorithms Juan Jose Garau-Luis, Yingjie Miao, John D Co-Reyes, Aaron Parisi, Jie Tan, Esteban Real, Aleksandra Faust

ICLRW 2021 Accelerating Online Reinforcement Learning via Model-Based Meta-Learning John D Co-Reyes, Sarah Feng, Glen Berseth, Jie Qui, Sergey Levine

ICLR 2021 Evolving Reinforcement Learning Algorithms John D Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V Le, Sergey Levine, Honglak Lee, Aleksandra Faust

ICMLW 2021 Intrinsic Control of Variational Beliefs in Dynamic Partially-Observed Visual Environments Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine

CoRL 2019 Entity Abstraction in Visual Model-Based Reinforcement Learning Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua Tenenbaum, Sergey Levine

ICLR 2019 Guiding Policies with Language via Meta-Learning John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, Jacob Andreas, John DeNero, Pieter Abbeel, Sergey Levine