Imitative Planning using Conditional Normalizing Flow. - Shubhankar Agarwal; Harshit Sikchi; Cole Gulino; Eric Wilkinson (CoRR, 2020)

Learning Off-Policy with Online Planning. - Harshit Sikchi; Wenxuan Zhou; David Held (CoRL, 2021)

Real Robot Challenge: A Robotics Competition in the Cloud. - Stefan Bauer; Manuel Wüthrich; Felix Widmaier; Annika Buchholz; Sebastian Stark; Anirudh Goyal; Thomas Steinbrenner; Joel Akpo; Shruti Joshi; Vincent Berenz; Vaibhav Agrawal; Niklas Funk; et al. (NeurIPS (Competition and Demos), 2021)

Lyapunov Barrier Policy Optimization. - Harshit Sikchi; Wenxuan Zhou; David Held (CoRR, 2021)

Real Robot Challenge 2021: Cartesian Position Control with Triangle Grasp and Trajectory Interpolation. - Rishabh Madan; Harshit Sikchi; Ethan K. Gordon; Tapomayukh Bhattacharjee (CoRR, 2022)

Imitation from Arbitrary Experience: A Dual Unification of Reinforcement and Imitation Learning Methods. - Harshit Sikchi; Amy Zhang 001; Scott Niekum (CoRR, 2023)

Contrastive Preference Learning: Learning from Human Feedback without RL. - Joey Hejna; Rafael Rafailov; Harshit Sikchi; Chelsea Finn; Scott Niekum; W. Bradley Knox; Dorsa Sadigh (CoRR, 2023)

A Ranking Game for Imitation Learning. - Harshit Sikchi; Akanksha Saran; Wonjoon Goo; Scott Niekum (Trans. Mach. Learn. Res., 2023)

A Dual Approach to Imitation Learning from Observations with Offline Datasets. - Harshit Sikchi; Caleb Chuck; Amy Zhang 001; Scott Niekum (CoRL, 2024)

Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning. - Joey Hejna; Rafael Rafailov; Harshit Sikchi; Chelsea Finn; Scott Niekum; W. Bradley Knox; Dorsa Sadigh (ICLR, 2024)

Score Models for Offline Goal-Conditioned Reinforcement Learning. - Harshit Sikchi; Rohan Chitnis; Ahmed Touati; Alborz Geramifard; Amy Zhang 001; Scott Niekum (ICLR, 2024)

Dual RL: Unification and New Methods for Reinforcement and Imitation Learning. - Harshit Sikchi; Qinqing Zheng; Amy Zhang 001; Scott Niekum (ICLR, 2024)

Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms. - Rafael Rafailov; Yaswanth Chittepu; Ryan Park; Harshit Sikchi; Joey Hejna; W. Bradley Knox; Chelsea Finn; Scott Niekum (NeurIPS, 2024)

Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning. - Caleb Chuck; Carl Qi; Michael J. Munje; Shuozhe Li; Max Rudolph; Chang Shi; Siddhant Agarwal; Harshit Sikchi; Abhinav Peri; Sarthak Dayal; Evan Kuo; Kavan Mehta; et al. (CoRR, 2024)

Proto Successor Measure: Representing the Space of All Possible Solutions of Reinforcement Learning. - Siddhant Agarwal; Harshit Sikchi; Peter Stone 001; Amy Zhang 001 (CoRR, 2024)

RL Zero: Zero-Shot Language to Behaviors without any Supervision. - Harshit Sikchi; Siddhant Agarwal; Pranaya Jajoo; Samyak Parajuli; Caleb Chuck; Max Rudolph; Peter Stone 001; Amy Zhang 001; Scott Niekum (CoRR, 2024)

An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning. - Haoran Xu 003; Shuozhe Li; Harshit Sikchi; Scott Niekum; Amy Zhang 001 (ICLR, 2025)

CREStE: Scalable Mapless Navigation with Internet Scale Priors and Counterfactual Guidance. - Arthur Zhang; Harshit Sikchi; Amy Zhang 001; Joydeep Biswas (CoRR, 2025)

Fast Adaptation with Behavioral Foundation Models. - Harshit Sikchi; Andrea Tirinzoni; Ahmed Touati; Yingchen Xu; Anssi Kanervisto; Scott Niekum; Amy Zhang 001; Alessandro Lazaric; Matteo Pirotta (CoRR, 2025)

CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation. - Kushal Gajjar; Harshit Sikchi; Arpit Singh Gautam; Marc Hammons; Saurabh Jha (CoRR, 2025)