Avi Singh - RankMe

40 papers A* 10Misc 4Journal 22Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Training Language Models to Self-Correct via Reinforcement Learning. ICLR 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 M. P. Behbahani, Aleksandra Faust
2024	J	`jnl`	Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. Trans. Mach. Learn. Res. 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 Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel
2024	A*	`conf`	Many-Shot In-Context Learning. NeurIPS Rishabh Agarwal, Avi Singh, Lei Zhang, Bernd Bohnet, Luis Rosias, Stephanie C. Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle
2024	J	`jnl`	Many-Shot In-Context Learning. CoRR Rishabh Agarwal, Avi Singh, Lei M. Zhang, Bernd Bohnet, Stephanie Chan, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle
2024	J	`jnl`	Training Language Models to Self-Correct via Reinforcement Learning. CoRR 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 M. P. Behbahani, Aleksandra Faust
2023	J	`jnl`	Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. CoRR Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron Parisi, Abhishek Kumar, Alex Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin F. Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel
2023	J	`jnl`	Improving Large Language Model Fine-tuning for Solving Math Problems. CoRR Yixin Liu, Avi Singh, C. Daniel Freeman, John D. Co-Reyes, Peter J. Liu
2023	—	`conf`	Robotic Table Tennis: A Case Study into a High Speed Learning System. Robotics: Science and Systems David B. D'Ambrosio, Navdeep Jaitly, Vikas Sindhwani, Ken Oslund, Peng Xu, Nevena Lazic, Anish Shankar, Tianli Ding, Jonathan Abelian, Erwin Coumans, Gus Kouretas, Thinh Nguyen, Justin Boyd, Atil Iscen, Reza Mahjourian, Vincent Vanhoucke, Alex Bewley, Yuheng Kuang, Michael Ahn, Deepali Jain, Satoshi Kataoka, Omar E. Cortes, Pierre Sermanet, Corey Lynch, Pannag R. Sanketi, Krzysztof Choromanski, Wenbo Gao, Juhana Kangaspunta, Krista Reymann, Grace Vesom, Sherry Q. Moore, Avi Singh, Saminda Wishwajith Abeyruwan, Laura Graesser
2023	J	`jnl`	Robotic Table Tennis: A Case Study into a High Speed Learning System. CoRR David B. D'Ambrosio, Jonathan Abelian, Saminda Abeyruwan, Michael Ahn, Alex Bewley, Justin Boyd, Krzysztof Choromanski, Omar Cortes, Erwin Coumans, Tianli Ding, Wenbo Gao, Laura Graesser, Atil Iscen, Navdeep Jaitly, Deepali Jain, Juhana Kangaspunta, Satoshi Kataoka, Gus Kouretas, Yuheng Kuang, Nevena Lazic, Corey Lynch, Reza Mahjourian, Sherry Q. Moore, Thinh Nguyen, Ken Oslund, Barney J. Reed, Krista Reymann, Pannag R. Sanketi, Anish Shankar, Pierre Sermanet, Vikas Sindhwani, Avi Singh, Vincent Vanhoucke, Grace Vesom, Peng Xu
2023	A*	`conf`	Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning. ICRA David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, Jake Varley
2022	Misc	`conf`	Don't Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning. CoRL Homer Walke, Jonathan Yang, Albert Yu, Aviral Kumar, Jedrzej Orbik, Avi Singh, Sergey Levine
2022	J	`jnl`	Don't Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning. CoRR Homer Walke, Jonathan Yang, Albert Yu, Aviral Kumar, Jedrzej Orbik, Avi Singh, Sergey Levine
2022	J	`jnl`	Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning. CoRR David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, Jake Varley
2022	Misc	`conf`	i-Sim2Real: Reinforcement Learning of Robotic Policies in Tight Human-Robot Interaction Loops. CoRL Saminda Wishwajith Abeyruwan, Laura Graesser, David B. D'Ambrosio, Avi Singh, Anish Shankar, Alex Bewley, Deepali Jain, Krzysztof Marcin Choromanski, Pannag R. Sanketi
2022	J	`jnl`	i-Sim2Real: Reinforcement Learning of Robotic Policies in Tight Human-Robot Interaction Loops. CoRR Saminda Abeyruwan, Laura Graesser, David B. D'Ambrosio, Avi Singh, Anish Shankar, Alex Bewley, Deepali Jain, Krzysztof Choromanski, Pannag R. Sanketi
2021	A*	`conf`	Parrot: Data-Driven Behavioral Priors for Reinforcement Learning. ICLR Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
2021	—	`—`	Real World Robot Learning: Learned Rewards, Offline Datasets and Skill Re-Use Avi Singh
2020	J	`jnl`	COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning. CoRR Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine
2020	Misc	`conf`	Chaining Behaviors from Data with Model-Free Reinforcement Learning. CoRL Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine
2020	J	`jnl`	Parrot: Data-Driven Behavioral Priors for Reinforcement Learning. CoRR Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
2020	A*	`conf`	Scalable Multi-Task Imitation Learning with Autonomous Improvement. ICRA Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, Chelsea Finn
2020	J	`jnl`	Scalable Multi-Task Imitation Learning with Autonomous Improvement. CoRR Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, Chelsea Finn
2020	A*	`conf`	The Ingredients of Real World Robotic Reinforcement Learning. ICLR Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine
2020	J	`jnl`	The Ingredients of Real-World Robotic Reinforcement Learning. CoRR Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine
2019	—	`conf`	End-To-End Robotic Reinforcement Learning without Reward Engineering. Robotics: Science and Systems Avi Singh, Larry Yang, Chelsea Finn, Sergey Levine
2019	J	`jnl`	End-to-End Robotic Reinforcement Learning without Reward Engineering. CoRR Avi Singh, Larry Yang, Kristian Hartikainen, Chelsea Finn, Sergey Levine
2019	J	`jnl`	Visual Dialog. IEEE Trans. Pattern Anal. Mach. Intell. Abhishek Das, Satwik Kottur, Khushi Gupta, Avi Singh, Deshraj Yadav, Stefan Lee, José M. F. Moura, Devi Parikh, Dhruv Batra
2018	—	`conf`	Divide-and-Conquer Reinforcement Learning. ICLR (Poster) Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine
2018	Misc	`conf`	Few-Shot Goal Inference for Visuomotor Learning and Planning. CoRL Annie Xie, Avi Singh, Sergey Levine, Chelsea Finn
2018	J	`jnl`	Few-Shot Goal Inference for Visuomotor Learning and Planning. CoRR Annie Xie, Avi Singh, Sergey Levine, Chelsea Finn
2018	A*	`conf`	Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. NeurIPS Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine
2018	J	`jnl`	Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. CoRR Justin Fu, Avi Singh, Dibya Ghosh, Larry Yang, Sergey Levine
2017	J	`jnl`	Divide-and-Conquer Reinforcement Learning. CoRR Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine
2017	A*	`conf`	GPLAC: Generalizing Vision-Based Robotic Skills Using Weakly Labeled Images. ICCV Avi Singh, Larry Yang, Sergey Levine
2017	J	`jnl`	GPLAC: Generalizing Vision-Based Robotic Skills using Weakly Labeled Images. CoRR Avi Singh, Larry Yang, Sergey Levine
2017	A*	`conf`	Visual Dialog. CVPR Abhishek Das, Satwik Kottur, Khushi Gupta, Avi Singh, Deshraj Yadav, José M. F. Moura, Devi Parikh, Dhruv Batra
2016	J	`jnl`	Brain4Cars: Car That Knows Before You Do via Sensory-Fusion Deep Learning Architecture. CoRR Ashesh Jain, Hema Swetha Koppula, Shane Soh, Bharad Raghavan, Avi Singh, Ashutosh Saxena
2016	A*	`conf`	Recurrent Neural Networks for driver activity anticipation via sensory-fusion architecture. ICRA Ashesh Jain, Avi Singh, Hema Swetha Koppula, Shane Soh, Ashutosh Saxena
2016	J	`jnl`	Visual Dialog. CoRR Abhishek Das, Satwik Kottur, Khushi Gupta, Avi Singh, Deshraj Yadav, José M. F. Moura, Devi Parikh, Dhruv Batra
2015	J	`jnl`	Recurrent Neural Networks for Driver Activity Anticipation via Sensory-Fusion Architecture. CoRR Ashesh Jain, Avi Singh, Hema Swetha Koppula, Shane Soh, Ashutosh Saxena