Archit Sharma

According to our database, Archit Sharma authored at least 33 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Towards Data-Centric RLHF: Simple Metrics for Preference Dataset Comparison.

Judy Hanwen Shen, Archit Sharma, Jun Qin

CoRR, 2024

Stream of Search (SoS): Learning to Search in Language.

Kanishk Gandhi, Denise Lee, Gabriel Grand, Muxin Liu, Winson Cheng, Archit Sharma, Noah D. Goodman

CoRR, 2024

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.

Alexander Khazatsky, Karl Pertsch, Suraj Nair, Ashwin Balakrishna, Sudeep Dasari, Siddharth Karamcheti, Soroush Nasiriany, Mohan Kumar Srirama, Lawrence Yunliang Chen, Kirsty Ellis, Peter David Fagan, Joey Hejna, Masha Itkina, Marion Lepert, Yecheng Jason Ma, Patrick Tree Miller, Jimmy Wu, Suneel Belkhale, Shivin Dass, Huy Ha, Arhan Jain, Abraham Lee, Youngwoon Lee, Marius Memmel, Sungjae Park, Ilija Radosavovic, Kaiyuan Wang, Albert Zhan, Kevin Black, Cheng Chi, Kyle Beltran Hatch, Shan Lin, Jingpei Lu, Jean Mercat, Abdul Rehman, Pannag R. Sanketi, Archit Sharma, Cody Simpson, Quan Vuong, Homer Rich Walke, Blake Wulfe, Ted Xiao, Jonathan Heewon Yang, Arefeh Yavary, Tony Z. Zhao, Christopher Agia, Rohan Baijal, Mateo Guaman Castro, Daphne Chen, Qiuyu Chen, Trinity Chung, Jaimyn Drake, Ethan Paul Foster, et al.

CoRR, 2024

Yell At Your Robot: Improving On-the-Fly from Language Corrections.

Lucy Xiaoyang Shi, Zheyuan Hu, Tony Z. Zhao, Archit Sharma, Karl Pertsch, Jianlan Luo, Sergey Levine, Chelsea Finn

CoRR, 2024

A Critical Evaluation of AI Feedback for Aligning Large Language Models.

Archit Sharma, Sedrick Keh, Eric Mitchell, Chelsea Finn, Kushal Arora, Thomas Kollar

CoRR, 2024

Robot Fine-Tuning Made Easy: Pre-Training Rewards and Policies for Autonomous Real-World Reinforcement Learning.

Jingyun Yang, Max Sobol Mark, Brandon Vu, Archit Sharma, Jeannette Bohg, Chelsea Finn

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration.

Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning.

Jianlan Luo, Zheyuan Hu, Charles Xu, You Liang Tan, Jacob Berg, Archit Sharma, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data.

Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar

Proceedings of the Forty-first International Conference on Machine Learning, 2024

RLVF: Learning from Verbal Feedback without Overgeneralization.

Moritz Stephan, Alexander Khazatsky, Eric Mitchell, Annie S. Chen, Sheryl Hsu, Archit Sharma, Chelsea Finn

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Language Model Detectors Are Easily Optimized Against.

Charlotte Nicks, Eric Mitchell, Rafael Rafailov, Archit Sharma, Christopher D. Manning, Chelsea Finn, Stefano Ermon

Proceedings of the Twelfth International Conference on Learning Representations, 2024

An Emulator for Fine-tuning Large Language Models using Small Language Models.

Eric Mitchell, Rafael Rafailov, Archit Sharma, Chelsea Finn, Christopher D. Manning

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Evolutionary Search of Optimal Hyperparameters for Learning Various Robot Manipulation Tasks.

Archit Sharma, Sandeep Gupta, Peeyush Thakur, Narendra Kumar Dhar, Laxmidhar Behera

Proceedings of the IEEE Congress on Evolutionary Computation, 2024

2023

Adapt On-the-Go: Behavior Modulation for Single-Life Robot Deployment.

Annie S. Chen, Govind Chada, Laura M. Smith, Archit Sharma, Zipeng Fu, Sergey Levine, Chelsea Finn

CoRR, 2023

Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration Bias.

Max Sobol Mark, Archit Sharma, Fahim Tajwar, Rafael Rafailov, Sergey Levine, Chelsea Finn

CoRR, 2023

Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D. Manning, Stefano Ermon, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback.

Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, Christopher D. Manning

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Waypoint-Based Imitation Learning for Robotic Manipulation.

Lucy Xiaoyang Shi, Archit Sharma, Tony Z. Zhao, Chelsea Finn

Proceedings of the Conference on Robot Learning, 2023

Self-Improving Robots: End-to-End Autonomous Visuomotor Reinforcement Learning.

Archit Sharma, Ahmed M. Ahmed, Rehaan Ahmad, Chelsea Finn

Proceedings of the Conference on Robot Learning, 2023

APTSumm at BioLaySumm Task 1: Biomedical Breakdown, Improving Readability by Relevancy Based Selection.

A. S. Poornash, Atharva Deshmukh, Archit Sharma, Sriparna Saha

Proceedings of the 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, 2023

2022

When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning.

Annie Xie, Fahim Tajwar, Archit Sharma, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

You Only Live Once: Single-Life Reinforcement Learning.

Annie S. Chen, Archit Sharma, Sergey Levine, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning.

Archit Sharma, Rehaan Ahmad, Chelsea Finn

Proceedings of the International Conference on Machine Learning, 2022

Autonomous Reinforcement Learning: Formalism and Benchmarking.

Archit Sharma, Kelvin Xu, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Persistent Reinforcement Learning via Subgoal Curricula.

Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn

CoRR, 2021

Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning.

Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu

CoRR, 2021

Discriminator Augmented Model-Based Reinforcement Learning.

Behzad Haghgoo, Allan Zhou, Archit Sharma, Chelsea Finn

CoRR, 2021

Autonomous Reinforcement Learning via Subgoal Curricula.

Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning.

Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning.

Archit Sharma, Michael Ahn, Sergey Levine, Vikash Kumar, Karol Hausman, Shixiang Gu

Proceedings of the Robotics: Science and Systems XVI, 2020

Dynamics-Aware Unsupervised Discovery of Skills.

Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, Karol Hausman

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

A flexible probabilistic framework for large-margin mixture of experts.

Archit Sharma, Siddhartha Saxena, Piyush Rai

Mach. Learn., 2019

2018

TrueChain: Highly Performant Decentralized Public Ledger.

Archit Sharma, Jasper L, Eric Zhang

CoRR, 2018