Gokul Swamy

According to our database, Gokul Swamy authored at least 26 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Justified or Just Convincing? Error Verifiability as a Dimension of LLM Quality.

Xiaoyuan Zhu, Kimberly Le Truong, Riccardo Fogliato, Gokul Swamy, Weijian Zhang, Ming-Hsuan Yang, Longtian Ye, Bangya Liu, Minghao Liu, Andrew Ilyas, Zhiwei Steven Wu

CoRR, April, 2026

Back to Blackwell: Closing the Loop on Intransitivity in Multi-Objective Preference Fine-Tuning.

Jiahao Zhang, Lujing Zhang, Keltin Grimes, Zhuohao Yu, Gokul Swamy, Zhiwei Steven Wu

CoRR, February, 2026

Gained in Translation: Privileged Pairwise Judges Enhance Multilingual Reasoning.

Lintang Sutawika, Gokul Swamy, Steven Wu, Graham Neubig

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

A Smooth Sea Never Made a Skilled SAILOR: Robust Imitation via Learning to Search.

Arnav Kumar Jain, Vibhakar Mohta, Subin Kim, Atiksh Bhardwaj, Juntao Ren, Yunhai Feng, Sanjiban Choudhury, Gokul Swamy

CoRR, June, 2025

Scaling Offline RL via Efficient and Expressive Shortcut Models.

Nicolas A. Espinosa Dice, Yiyi Zhang, Yiding Chen, Bradley Guo, Owen Oertell, Gokul Swamy, Kianté Brantley, Wen Sun

CoRR, May, 2025

All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning.

Gokul Swamy, Sanjiban Choudhury, Wen Sun, Zhiwei Steven Wu, J. Andrew Bagnell

CoRR, March, 2025

Diffusing States and Matching Scores: A New Framework for Imitation Learning.

Runzhe Wu, Yiding Chen, Gokul Swamy, Kianté Brantley, Wen Sun

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF.

Zhaolin Gao, Wenhao Zhan, Jonathan Daniel Chang, Gokul Swamy, Kianté Brantley, Jason D. Lee, Wen Sun

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Efficient Imitation under Misspecification.

Nicolas A. Espinosa Dice, Sanjiban Choudhury, Wen Sun, Gokul Swamy

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Understanding Preference Fine-Tuning Through the Lens of Coverage.

Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun

CoRR, 2024

Multi-Agent Imitation Learning: Value is Easy, Regret is Hard.

Jingwu Tang, Gokul Swamy, Fei Fang, Zhiwei Steven Wu

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

REBEL: Reinforcement Learning via Regressing Relative Rewards.

Zhaolin Gao, Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, Drew Bagnell, Jason D. Lee, Wen Sun

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

The Importance of Online Data: Understanding Preference Fine-tuning via Coverage.

Yuda Song, Gokul Swamy, Aarti Singh, J. Andrew Bagnell, Wen Sun

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

A Minimaximalist Approach to Reinforcement Learning from Human Feedback.

Gokul Swamy, Christoph Dann, Rahul Kidambi, Steven Wu, Alekh Agarwal

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Hybrid Inverse Reinforcement Learning.

Juntao Ren, Gokul Swamy, Steven Wu, Drew Bagnell, Sanjiban Choudhury

Proceedings of the Forty-first International Conference on Machine Learning, 2024

When is Transfer Learning Possible?

My Phan, Kianté Brantley, Stephanie Milani, Soroush Mehri, Gokul Swamy, Geoffrey J. Gordon

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Inverse Reinforcement Learning without Reinforcement Learning.

Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu

CoRR, 2023

Learning Shared Safety Constraints from Multi-task Demonstrations.

Konwoo Kim, Gokul Swamy, Zuxin Liu, Ding Zhao, Sanjiban Choudhury, Zhiwei Steven Wu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Inverse Reinforcement Learning without Reinforcement Learning.

Gokul Swamy, David Wu, Sanjiban Choudhury, Drew Bagnell, Zhiwei Steven Wu

Proceedings of the International Conference on Machine Learning, 2023

2022

Game-Theoretic Algorithms for Conditional Moment Matching.

Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu

CoRR, 2022

Minimax Optimal Online Imitation Learning via Replay Estimation.

Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu, Jiantao Jiao, Kannan Ramchandran

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sequence Model Imitation Learning with Unobserved Contexts.

Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Causal Imitation Learning under Temporally Correlated Noise.

Gokul Swamy, Sanjiban Choudhury, Drew Bagnell, Steven Wu

Proceedings of the International Conference on Machine Learning, 2022

2021

A Critique of Strictly Batch Imitation Learning.

Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu

CoRR, 2021

Of Moments and Matching: Trade-offs and Treatments in Imitation Learning.

Gokul Swamy, Sanjiban Choudhury, Zhiwei Steven Wu, J. Andrew Bagnell

CoRR, 2021

Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap.

Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu

Proceedings of the 38th International Conference on Machine Learning, 2021