TrueChain: Highly Performant Decentralized Public Ledger. - Archit Sharma; Jasper L; Eric Zhang (CoRR, 2018)

A flexible probabilistic framework for large-margin mixture of experts. - Archit Sharma; Siddhartha Saxena; Piyush Rai (Mach. Learn., 2019)

Dynamics-Aware Unsupervised Discovery of Skills. - Archit Sharma; Shixiang Gu; Sergey Levine; Vikash Kumar; Karol Hausman (ICLR, 2020)

Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning. - Archit Sharma; Michael Ahn; Sergey Levine; Vikash Kumar; Karol Hausman; Shixiang Gu (Robotics: Science and Systems, 2020)

Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning. - Jongwook Choi; Archit Sharma; Honglak Lee; Sergey Levine; Shixiang Shane Gu (ICML, 2021)

Autonomous Reinforcement Learning via Subgoal Curricula. - Archit Sharma; Abhishek Gupta 004; Sergey Levine; Karol Hausman; Chelsea Finn (NeurIPS, 2021)

Discriminator Augmented Model-Based Reinforcement Learning. - Behzad Haghgoo; Allan Zhou; Archit Sharma; 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)

Persistent Reinforcement Learning via Subgoal Curricula. - Archit Sharma; Abhishek Gupta 004; Sergey Levine; Karol Hausman; Chelsea Finn (CoRR, 2021)

Autonomous Reinforcement Learning: Formalism and Benchmarking. - Archit Sharma; Kelvin Xu; Nikhil Sardana; Abhishek Gupta 004; Karol Hausman; Sergey Levine; Chelsea Finn (ICLR, 2022)

A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning. - Archit Sharma; Rehaan Ahmad; Chelsea Finn (ICML, 2022)

You Only Live Once: Single-Life Reinforcement Learning. - Annie S. Chen; Archit Sharma; Sergey Levine; Chelsea Finn (NeurIPS, 2022)

When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning. - Annie Xie; Fahim Tajwar; Archit Sharma; Chelsea Finn (NeurIPS, 2022)

APTSumm at BioLaySumm Task 1: Biomedical Breakdown, Improving Readability by Relevancy Based Selection. - A. S. Poornash; Atharva Deshmukh; Archit Sharma; Sriparna Saha 001 (BioNLP@ACL, 2023)

Self-Improving Robots: End-to-End Autonomous Visuomotor Reinforcement Learning. - Archit Sharma; Ahmed M. Ahmed 004; Rehaan Ahmad; Chelsea Finn (CoRL, 2023)

Waypoint-Based Imitation Learning for Robotic Manipulation. - Lucy Xiaoyang Shi; Archit Sharma; Tony Z. Zhao; Chelsea Finn (CoRL, 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 (EMNLP, 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 (NeurIPS, 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)

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)

Evolutionary Search of Optimal Hyperparameters for Learning Various Robot Manipulation Tasks. - Archit Sharma; Sandeep Gupta 003; Peeyush Thakur; Narendra Kumar Dhar; Laxmidhar Behera (CEC, 2024)

An Emulator for Fine-tuning Large Language Models using Small Language Models. - Eric Mitchell; Rafael Rafailov; Archit Sharma; Chelsea Finn; Christopher D. Manning (ICLR, 2024)

Language Model Detectors Are Easily Optimized Against. - Charlotte Nicks; Eric Mitchell; Rafael Rafailov; Archit Sharma; Christopher D. Manning; Chelsea Finn; Stefano Ermon (ICLR, 2024)

RLVF: Learning from Verbal Feedback without Overgeneralization. - Moritz Stephan; Alexander Khazatsky; Eric Mitchell; Annie S. Chen; Sheryl Hsu; Archit Sharma; Chelsea Finn (ICML, 2024)

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data. - Fahim Tajwar; Anikait Singh; Archit Sharma; Rafael Rafailov; Jeff Schneider 001; Tengyang Xie; Stefano Ermon; Chelsea Finn; Aviral Kumar (ICML, 2024)

SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning. - Jianlan Luo; Zheyuan Hu 003; Charles Xu 003; You Liang Tan; Jacob Berg; Archit Sharma; Stefan Schaal; Chelsea Finn; Abhishek Gupta 004; Sergey Levine (ICRA, 2024)

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. - Abby O'Neill; Abdul Rehman; Abhiram Maddukuri; Abhishek Gupta 004; Abhishek Padalkar; Abraham Lee; Acorn Pooley; Agrim Gupta; Ajay Mandlekar; Ajinkya Jain; Albert Tung; Alex Bewley; et al. (ICRA, 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 (ICRA, 2024)

A Critical Evaluation of AI Feedback for Aligning Large Language Models. - Archit Sharma; Sedrick Scott Keh; Eric Mitchell; Chelsea Finn; Kushal Arora; Thomas Kollar (NeurIPS, 2024)

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. - Alexander Khazatsky; Karl Pertsch; Suraj Nair 003; Ashwin Balakrishna; Sudeep Dasari; Siddharth Karamcheti; Soroush Nasiriany; Mohan Kumar Srirama; Lawrence Yunliang Chen; Kirsty Ellis; Peter David Fagan; Joey Hejna; et al. (Robotics: Science and Systems, 2024)

Yell At Your Robot: Improving On-the-Fly from Language Corrections. - Lucy Xiaoyang Shi; Zheyuan Hu 003; Tony Z. Zhao; Archit Sharma; Karl Pertsch; Jianlan Luo; Sergey Levine; Chelsea Finn (Robotics: Science and Systems, 2024)

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. - Alexander Khazatsky; Karl Pertsch; Suraj Nair 003; Ashwin Balakrishna; Sudeep Dasari; Siddharth Karamcheti; Soroush Nasiriany; Mohan Kumar Srirama; Lawrence Yunliang Chen; Kirsty Ellis; Peter David Fagan; Joey Hejna; et al. (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)

Towards Data-Centric RLHF: Simple Metrics for Preference Dataset Comparison. - Judy Hanwen Shen; Archit Sharma; Jun Qin (CoRR, 2024)

Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone. - Max Sobol Mark; Tian Gao; Georgia Gabriela Sampaio; Mohan Kumar Srirama; Archit Sharma; Chelsea Finn; Aviral Kumar (CoRR, 2024)

Test-Time Alignment via Hypothesis Reweighting. - Yoonho Lee 001; Jonathan Williams; Henrik Marklund; Archit Sharma; Eric Mitchell; Anikait Singh; Chelsea Finn (CoRR, 2024)

Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval. - Sheryl Hsu; Omar Khattab; Chelsea Finn; Archit Sharma (ICLR, 2025)

FSPO: Few-Shot Preference Optimization of Synthetic Preference Data in LLMs Elicits Effective Personalization to Real Users. - Anikait Singh; Sheryl Hsu; Kyle Hsu; Eric Mitchell; Stefano Ermon; Tatsunori Hashimoto; Archit Sharma; Chelsea Finn (CoRR, 2025)