Jonathan D. Chang

28 papers A* 6A 1Journal 17Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	KARL: Knowledge Agents via Reinforcement Learning. CoRR Jonathan D. Chang, Andrew Drozdov, Shubham Toshniwal, Owen Oertell, Alexander Trott, Jacob P. Portes, Abhay Gupta, Pallavi Koppol, Ashutosh Baheti, Sean Kulinski, Ivan Zhou, Irene Dea, Krista Opsahl-Ong, Simon Favreau-Lessard, Sean Owen, Jose Javier Gonzalez Ortiz, Arnav Singhvi, Xabi Andrade, Cindy Wang, Kartik Sreenivasan, Sam Havens, Jialu Liu, Peyton DeNiro, Wen Sun, Michael Bendersky, Jonathan Frankle
2026	J	`jnl`	LLMs Can Learn to Reason Via Off-Policy RL. CoRR Daniel Ritter, Owen Oertell, Bradley Guo, Jonathan D. Chang, Kianté Brantley, Wen Sun
2025	J	`jnl`	Q♯: Provably Optimal Distributional RL for LLM Post-Training. CoRR Jin Peng Zhou, Kaiwen Wang, Jonathan D. Chang, Zhaolin Gao, Nathan Kallus, Kilian Q. Weinberger, Kianté Brantley, Wen Sun
2025	J	`jnl`	Value-Guided Search for Efficient Chain-of-Thought Reasoning. CoRR Kaiwen Wang, Jin Peng Zhou, Jonathan D. Chang, Zhaolin Gao, Nathan Kallus, Kianté Brantley, Wen Sun
2024	A*	`conf`	Adversarial Imitation Learning via Boosting. ICLR Jonathan D. Chang, Dhruv Sreenivas, Yingbing Huang, Kianté Brantley, Wen Sun
2024	J	`jnl`	Adversarial Imitation Learning via Boosting. CoRR Jonathan D. Chang, Dhruv Sreenivas, Yingbing Huang, Kianté Brantley, Wen Sun
2024	J	`jnl`	Critique-out-Loud Reward Models. CoRR Zachary Ankner, Mansheej Paul, Brandon Cui, Jonathan D. Chang, Prithviraj Ammanabrolu
2024	J	`jnl`	Dataset Reset Policy Optimization for RLHF. CoRR Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Kianté Brantley, Dipendra Misra, Jason D. Lee, Wen Sun
2024	A*	`conf`	REBEL: Reinforcement Learning via Regressing Relative Rewards. NeurIPS Zhaolin Gao, Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, Drew Bagnell, Jason D. Lee, Wen Sun
2024	J	`jnl`	REBEL: Reinforcement Learning via Regressing Relative Rewards. CoRR Zhaolin Gao, Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, J. Andrew Bagnell, Jason D. Lee, Wen Sun
2024	J	`jnl`	RL for Consistency Models: Faster Reward Guided Text-to-Image Generation. CoRR Owen Oertell, Jonathan D. Chang, Yiyi Zhang, Kianté Brantley, Wen Sun
2024	J	`jnl`	RL for Consistency Models: Reward Guided Text-to-Image Generation with Fast Inference. RLJ Owen Oertell, Jonathan D. Chang, Yiyi Zhang, Kianté Brantley, Wen Sun
2024	J	`jnl`	Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF. CoRR Zhaolin Gao, Wenhao Zhan, Jonathan D. Chang, Gokul Swamy, Kianté Brantley, Jason D. Lee, Wen Sun
2023	J	`jnl`	Learning to Generate Better Than Your LLM. CoRR Jonathan D. Chang, Kianté Brantley, Rajkumar Ramamurthy, Dipendra Misra, Wen Sun
2023	J	`jnl`	Policy-Gradient Training of Language Models for Ranking. CoRR Ge Gao, Jonathan D. Chang, Claire Cardie, Kianté Brantley, Thorsten Joachims
2022	A*	`conf`	Learning Bellman Complete Representations for Offline Policy Evaluation. ICML Jonathan D. Chang, Kaiwen Wang, Nathan Kallus, Wen Sun
2022	J	`jnl`	Learning Bellman Complete Representations for Offline Policy Evaluation. CoRR Jonathan D. Chang, Kaiwen Wang, Nathan Kallus, Wen Sun
2021	A*	`conf`	Mitigating Covariate Shift in Imitation Learning via Offline Data With Partial Coverage. NeurIPS Jonathan D. Chang, Masatoshi Uehara, Dhruv Sreenivas, Rahul Kidambi, Wen Sun
2021	J	`jnl`	Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great Coverage. CoRR Jonathan D. Chang, Masatoshi Uehara, Dhruv Sreenivas, Rahul Kidambi, Wen Sun
2021	A*	`conf`	MobILE: Model-Based Imitation Learning From Observation Alone. NeurIPS Rahul Kidambi, Jonathan D. Chang, Wen Sun
2021	J	`jnl`	Optimism is All You Need: Model-Based Imitation Learning From Observation Alone. CoRR Rahul Kidambi, Jonathan D. Chang, Wen Sun
2014	—	`conf`	Learning a Concept Hierarchy from Multi-labeled Documents. NIPS Viet-An Nguyen, Jordan L. Boyd-Graber, Philip Resnik, Jonathan D. Chang
2011	—	`—`	Uncovering, Understanding, and Predicting Links Jonathan D. Chang
2010	J	`jnl`	Erratum: SGDQN is Less Careful than Expected. J. Mach. Learn. Res. Antoine Bordes, Léon Bottou, Patrick Gallinari, Jonathan D. Chang, S. Alex Smith
2009	A*	`conf`	Connections between the lines: augmenting social networks with text. KDD Jonathan D. Chang, Jordan L. Boyd-Graber, David M. Blei
2009	—	`conf`	Reading Tea Leaves: How Humans Interpret Topic Models. NIPS Jonathan D. Chang, Jordan L. Boyd-Graber, Sean Gerrish, Chong Wang, David M. Blei
2009	A	`conf`	Relational Topic Models for Document Networks. AISTATS Jonathan D. Chang, David M. Blei
2007	—	`conf`	PU-BCD: Exponential Family Models for the Coarse- and Fine-Grained All-Words Tasks. SemEval@ACL Jonathan D. Chang, Miroslav Dudík, David M. Blei