RoboBrain: Large-Scale Knowledge Engine for Robots. - Ashutosh Saxena; Ashesh Jain; Ozan Sener; Aditya Jami; Dipendra Kumar Misra; Hema Swetha Koppula (CoRR, 2014)

Environment-Driven Lexicon Induction for High-Level Instructions. - Dipendra Kumar Misra; Kejia Tao; Percy Liang; Ashutosh Saxena (ACL (1), 2015)

Neural Shift-Reduce CCG Semantic Parsing. - Dipendra Kumar Misra; Yoav Artzi (EMNLP, 2016)

Tell me Dave: Context-sensitive grounding of natural language to manipulation instructions. - Dipendra Kumar Misra; Jaeyong Sung; Kevin Lee; Ashutosh Saxena (Int. J. Robotics Res., 2016)

Mapping Instructions and Visual Observations to Actions with Reinforcement Learning. - Dipendra Kumar Misra; John Langford 001; Yoav Artzi (EMNLP, 2017)

Mapping Navigation Instructions to Continuous Control Actions with Position-Visitation Prediction. - Valts Blukis; Dipendra Kumar Misra; Ross A. Knepper; Yoav Artzi (CoRL, 2018)

Mapping Instructions to Actions in 3D Environments with Visual Goal Prediction. - Dipendra Kumar Misra; Andrew Bennett; Valts Blukis; Eyvind Niklasson; Max Shatkhin; Yoav Artzi (EMNLP, 2018)

Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations. - Dipendra Misra; Ming-Wei Chang; Xiaodong He 001; Wen-tau Yih (EMNLP, 2018)

Lipschitz Continuity in Model-based Reinforcement Learning. - Kavosh Asadi; Dipendra Misra; Michael L. Littman (ICML, 2018)

CHALET: Cornell House Agent Learning Environment. - Claudia Yan; Dipendra Kumar Misra; Andrew Bennett; Aaron Walsman; Yonatan Bisk; Yoav Artzi (CoRR, 2018)

Equivalence Between Wasserstein and Value-Aware Model-based Reinforcement Learning. - Kavosh Asadi; Evan Cater; Dipendra Misra; Michael L. Littman (CoRR, 2018)

Towards a Simple Approach to Multi-step Model-based Reinforcement Learning. - Kavosh Asadi; Evan Cater; Dipendra Misra; Michael L. Littman (CoRR, 2018)

TOUCHDOWN: Natural Language Navigation and Spatial Reasoning in Visual Street Environments. - Howard Chen 003; Alane Suhr; Dipendra Misra; Noah Snavely; Yoav Artzi (CVPR, 2019)

EARLY FUSION for Goal Directed Robotic Vision. - Aaron Walsman; Yonatan Bisk; Saadia Gabriel; Dipendra Misra; Yoav Artzi; Yejin Choi 001; Dieter Fox (IROS, 2019)

Combating the Compounding-Error Problem with a Multi-step Model. - Kavosh Asadi; Dipendra Misra; Seungchan Kim; Michael L. Littman (CoRR, 2019)

Scalable and Interpretable Approaches for Learning to Follow Natural Language Instructions. - Dipendra Misra (2019)

Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning. - Dipendra Misra; Mikael Henaff; Akshay Krishnamurthy; John Langford 001 (ICML, 2020)

Learning the Linear Quadratic Regulator from Nonlinear Observations. - Zakaria Mhammedi; Dylan J. Foster; Max Simchowitz; Dipendra Misra; Wen Sun 002; Akshay Krishnamurthy; Alexander Rakhlin; John Langford 001 (NeurIPS, 2020)

Provable Rich Observation Reinforcement Learning with Combinatorial Latent States. - Dipendra Misra; Qinghua Liu; Chi Jin 001; John Langford 001 (ICLR, 2021)

Interactive Learning from Activity Description. - Khanh Nguyen; Dipendra Misra; Robert E. Schapire; Miroslav Dudík; Patrick Shafto (ICML, 2021)

Have you tried Neural Topic Models? Comparative Analysis of Neural and Non-Neural Topic Models with Application to COVID-19 Twitter Data. - Andrew Bennett; Dipendra Misra; Nga Than (CoRR, 2021)

Provable RL with Exogenous Distractors via Multistep Inverse Dynamics. - Yonathan Efroni; Dipendra Misra; Akshay Krishnamurthy; Alekh Agarwal; John Langford 001 (CoRR, 2021)

Investigating the Role of Negatives in Contrastive Representation Learning. - Jordan T. Ash; Surbhi Goel; Akshay Krishnamurthy; Dipendra Misra (AISTATS, 2022)

Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information. - Yonathan Efroni; Dylan J. Foster; Dipendra Misra; Akshay Krishnamurthy; John Langford 001 (COLT, 2022)

Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics. - Yonathan Efroni; Dipendra Misra; Akshay Krishnamurthy; Alekh Agarwal; John Langford 001 (ICLR, 2022)

Understanding Contrastive Learning Requires Incorporating Inductive Biases. - Nikunj Saunshi; Jordan T. Ash; Surbhi Goel; Dipendra Misra; Cyril Zhang; Sanjeev Arora; Sham M. Kakade; Akshay Krishnamurthy (ICML, 2022)

Provably sample-efficient RL with side information about latent dynamics. - Yao Liu; Dipendra Misra; Miro Dudík; Robert E. Schapire (NeurIPS, 2022)

Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models. - Alex Lamb; Riashat Islam; Yonathan Efroni; Aniket Didolkar; Dipendra Misra; Dylan J. Foster; Lekan P. Molu; Rajan Chari; Akshay Krishnamurthy; John Langford 001 (CoRR, 2022)

Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information. - Riashat Islam; Manan Tomar; Alex Lamb; Yonathan Efroni; Hongyu Zang; Aniket Didolkar; Dipendra Misra; Xin Li 033; Harm van Seijen; Remi Tachet des Combes; John Langford 001 (CoRR, 2022)

Towards Data-Driven Offline Simulations for Online Reinforcement Learning. - Shengpu Tang; Felipe Vieira Frujeri; Dipendra Misra; Alex Lamb; John Langford 001; Paul Mineiro; Sebastian Kochman (CoRR, 2022)

Provable Safe Reinforcement Learning with Binary Feedback. - Andrew Bennett; Dipendra Misra; Nathan Kallus (AISTATS, 2023)

Principled Offline RL in the Presence of Rich Exogenous Information. - Riashat Islam; Manan Tomar; Alex Lamb; Yonathan Efroni; Hongyu Zang; Aniket Rajiv Didolkar; Dipendra Misra; Xin Li 033; Harm van Seijen; Remi Tachet des Combes; John Langford 001 (ICML, 2023)

Survival Instinct in Offline Reinforcement Learning. - Anqi Li 001; Dipendra Misra; Andrey Kolobov; Ching-An Cheng (NeurIPS, 2023)

Learning to Generate Better Than Your LLM. - Jonathan D. Chang; Kianté Brantley; Rajkumar Ramamurthy; Dipendra Misra; Wen Sun 002 (CoRR, 2023)

LLF-Bench: Benchmark for Interactive Learning from Language Feedback. - Ching-An Cheng; Andrey Kolobov; Dipendra Misra; Allen Nie; Adith Swaminathan (CoRR, 2023)

Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models. - Alex Lamb; Riashat Islam; Yonathan Efroni; Aniket Rajiv Didolkar; Dipendra Misra; Dylan J. Foster; Lekan P. Molu; Rajan Chari; Akshay Krishnamurthy; John Langford 001 (Trans. Mach. Learn. Res., 2023)

Towards Principled Representation Learning from Videos for Reinforcement Learning. - Dipendra Misra; Akanksha Saran; Tengyang Xie; Alex Lamb; John Langford 001 (ICLR, 2024)

The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction. - Pratyusha Sharma; Jordan T. Ash; Dipendra Misra (ICLR, 2024)

Provable Interactive Learning with Hindsight Instruction Feedback. - Dipendra Misra; Aldo Pacchiano; Robert E. Schapire (ICML, 2024)

Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning. - Dylan J. Foster; Adam Block; Dipendra Misra (NeurIPS, 2024)

Aligning LLM Agents by Learning Latent Preference from User Edits. - Ge Gao; Alexey Taymanov; Eduardo Salinas; Paul Mineiro; Dipendra Misra (NeurIPS, 2024)

Policy Improvement using Language Feedback Models. - Victor Zhong; Dipendra Misra; Xingdi Yuan; Marc-Alexandre Côté (NeurIPS, 2024)

Dataset Reset Policy Optimization for RLHF. - Jonathan D. Chang; Wenhao Zhan; Owen Oertell; Kianté Brantley; Dipendra Misra; Jason D. Lee; Wen Sun 002 (CoRR, 2024)