Ensemble Maximum Entropy Classification and Linear Regression for Author Age Prediction. - Joey Hong; Chris A. Mattmann; Paul M. Ramirez (IRI, 2017)

Rules of the Road: Predicting Driving Behavior With a Convolutional Model of Semantic Interactions. - Joey Hong; Benjamin Sapp; James Philbin (CVPR, 2019)

Latent Bandits Revisited. - Joey Hong; Branislav Kveton; Manzil Zaheer; Yinlam Chow; Amr Ahmed 001; Craig Boutilier (NeurIPS, 2020)

Piecewise-Stationary Off-Policy Optimization. - Joey Hong; Branislav Kveton; Manzil Zaheer; Yinlam Chow; Amr Ahmed 001 (CoRR, 2020)

Non-Stationary Latent Bandits. - Joey Hong; Branislav Kveton; Manzil Zaheer; Yinlam Chow; Amr Ahmed 001; Mohammad Ghavamzadeh; Craig Boutilier (CoRR, 2020)

Non-Stationary Off-Policy Optimization. - Joey Hong; Branislav Kveton; Manzil Zaheer; Yinlam Chow; Amr Ahmed 001 (AISTATS, 2021)

Latent Programmer: Discrete Latent Codes for Program Synthesis. - Joey Hong; David Dohan; Rishabh Singh; Charles Sutton; Manzil Zaheer (ICML, 2021)

Hierarchical Bayesian Bandits. - Joey Hong; Branislav Kveton; Manzil Zaheer; Mohammad Ghavamzadeh (AISTATS, 2022)

Thompson Sampling with a Mixture Prior. - Joey Hong; Branislav Kveton; Manzil Zaheer; Mohammad Ghavamzadeh; Craig Boutilier (AISTATS, 2022)

Should I Run Offline Reinforcement Learning or Behavioral Cloning? - Aviral Kumar; Joey Hong; Anikait Singh; Sergey Levine (ICLR, 2022)

Deep Hierarchy in Bandits. - Joey Hong; Branislav Kveton; Sumeet Katariya; Manzil Zaheer; Mohammad Ghavamzadeh (ICML, 2022)

Compositional Generalization and Decomposition in Neural Program Synthesis. - Kensen Shi; Joey Hong; Manzil Zaheer; Pengcheng Yin; Charles Sutton (CoRR, 2022)

When Should We Prefer Offline Reinforcement Learning Over Behavioral Cloning? - Aviral Kumar; Joey Hong; Anikait Singh; Sergey Levine (CoRR, 2022)

On the Sensitivity of Reward Inference to Misspecified Human Models. - Joey Hong; Kush Bhatia; Anca D. Dragan (ICLR, 2023)

Confidence-Conditioned Value Functions for Offline Reinforcement Learning. - Joey Hong; Aviral Kumar; Sergey Levine (ICLR, 2023)

Multi-Task Off-Policy Learning from Bandit Feedback. - Joey Hong; Branislav Kveton; Manzil Zaheer; Sumeet Katariya; Mohammad Ghavamzadeh (ICML, 2023)

Learning to Influence Human Behavior with Offline Reinforcement Learning. - Joey Hong; Sergey Levine; Anca D. Dragan (NeurIPS, 2023)

ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis. - Kensen Shi; Joey Hong; Manzil Zaheer; Pengcheng Yin; Charles Sutton (CoRR, 2023)

Zero-Shot Goal-Directed Dialogue via RL on Imagined Conversations. - Joey Hong; Sergey Levine; Anca D. Dragan (CoRR, 2023)

LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models. - Marwa Abdulhai; Isadora White; Charlie Snell; Charles Sun; Joey Hong; Yuexiang Zhai; Kelvin Xu; Sergey Levine (CoRR, 2023)

Offline RL with Observation Histories: Analyzing and Improving Sample Complexity. - Joey Hong; Anca D. Dragan; Sergey Levine (ICLR, 2024)

ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis. - Kensen Shi; Joey Hong; Yinlin Deng; Pengcheng Yin; Manzil Zaheer; Charles Sutton (ICLR, 2024)

Learning to Explore in POMDPs with Informational Rewards. - Annie Xie; Logan M. Bhamidipaty; Evan Zheran Liu; Joey Hong; Sergey Levine; Chelsea Finn (ICML, 2024)

Strategically Conservative Q-Learning. - Yutaka Shimizu; Joey Hong; Sergey Levine; Masayoshi Tomizuka (CoRR, 2024)

Interactive Dialogue Agents via Reinforcement Learning on Hindsight Regenerations. - Joey Hong; Jessica Lin; Anca D. Dragan; Sergey Levine (CoRR, 2024)

Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning. - Joey Hong; Anca D. Dragan; Sergey Levine (ICLR, 2025)

Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RL. - Joey Hong; Anca D. Dragan; Sergey Levine (CoRR, 2025)