A Hierarchical Approach to Scaling Batch Active Search Over Structured Data. - Vivek Myers; Peyton Greenside (CoRR, 2020)

Learning Multimodal Rewards from Rankings. - Vivek Myers; Erdem Biyik; Nima Anari; Dorsa Sadigh (CoRL, 2021)

Bayesian Meta-Learning Through Variational Gaussian Processes. - Vivek Myers; Nikhil Sardana (CoRR, 2021)

Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. - Vivek Myers; Andre Wang He; Kuan Fang; Homer Rich Walke; Philippe Hansen-Estruch; Ching-An Cheng; Mihai Jalobeanu; Andrey Kolobov; Anca D. Dragan; Sergey Levine (CoRL, 2023)

BridgeData V2: A Dataset for Robot Learning at Scale. - Homer Rich Walke; Kevin Black; Tony Z. Zhao; Quan Vuong; Chongyi Zheng; Philippe Hansen-Estruch; Andre Wang He; Vivek Myers; Moo Jin Kim; Max Du; Abraham Lee; Kuan Fang; et al. (CoRL, 2023)

Active Reward Learning from Online Preferences. - Vivek Myers; Erdem Biyik; Dorsa Sadigh (ICRA, 2023)

Toward Grounded Social Reasoning. - Minae Kwon; Hengyuan Hu; Vivek Myers; Siddharth Karamcheti; Anca D. Dragan; Dorsa Sadigh (CoRR, 2023)

Policy Adaptation via Language Optimization: Decomposing Tasks for Few-Shot Imitation. - Vivek Myers; Chunyuan Zheng; Oier Mees; Kuan Fang; Sergey Levine (CoRL, 2024)

Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. - Vivek Myers; Chongyi Zheng; Anca D. Dragan; Sergey Levine; Benjamin Eysenbach (ICML, 2024)

Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation. - Michelle Pan; Mariah L. Schrum; Vivek Myers; Erdem Biyik; Anca D. Dragan (ICML, 2024)

Toward Grounded Commonsense Reasoning. - Minae Kwon; Hengyuan Hu; Vivek Myers; Siddharth Karamcheti; Anca D. Dragan; Dorsa Sadigh (ICRA, 2024)

Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference. - Benjamin Eysenbach; Vivek Myers; Ruslan Salakhutdinov; Sergey Levine (NeurIPS, 2024)

Learning to Assist Humans without Inferring Rewards. - Vivek Myers; Evan Ellis; Sergey Levine; Benjamin Eysenbach; Anca D. Dragan (NeurIPS, 2024)

Accelerating Goal-Conditioned RL Algorithms and Research. - Michal Bortkiewicz; Wladek Palucki; Vivek Myers; Tadeusz Dziarmaga; Tomasz Arczewski; Lukasz Kucinski; Benjamin Eysenbach (CoRR, 2024)

Policy Adaptation via Language Optimization: Decomposing Tasks for Few-Shot Imitation. - Vivek Myers; Bill Chunyuan Zheng; Oier Mees; Sergey Levine; Kuan Fang (CoRR, 2024)

Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research. - Michal Bortkiewicz; Wladyslaw Palucki; Vivek Myers; Tadeusz Dziarmaga; Tomasz Arczewski; Lukasz Kucinski; Benjamin Eysenbach (ICLR, 2025)

Horizon Generalization in Reinforcement Learning. - Vivek Myers; Catherine Ji; Benjamin Eysenbach (ICLR, 2025)

Temporal Representation Alignment: Successor Features Enable Emergent Compositionality in Robot Instruction Following. - Vivek Myers; Bill Chunyuan Zheng; Anca D. Dragan; Kuan Fang; Sergey Levine (CoRR, 2025)

Multi-Agent Inverse Q-Learning from Demonstrations. - Nathaniel Haynam; Adam Khoja; Dhruv Kumar 009; Vivek Myers; Erdem Biyik (CoRR, 2025)