Fahim Tajwar

According to our database, Fahim Tajwar authored at least 17 papers between 2021 and 2026.

Collaborative distances:

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

2026

Retrospective In-Context Learning for Temporal Credit Assignment with Large Language Models.

Wen-Tse Chen, Jiayu Chen, Fahim Tajwar, Hao Zhu, Xintong Duan, Ruslan Salakhutdinov, Jeff G. Schneider

CoRR, February, 2026

Maximum Likelihood Reinforcement Learning.

Fahim Tajwar, Guanning Zeng, Yueer Zhou, Yuda Song, Daman Arora, Yiding Jiang, Jeff G. Schneider, Ruslan Salakhutdinov, Haiwen Feng, Andrea Zanette

CoRR, February, 2026

Expanding the Capabilities of Reinforcement Learning via Text Feedback.

Yuda Song, Lili Chen, Fahim Tajwar, Rémi Munos, Deepak Pathak, J. Andrew Bagnell, Aarti Singh, Andrea Zanette

CoRR, February, 2026

2025

Accelerating Diffusion Models in Offline RL via Reward-Aware Consistency Trajectory Distillation.

Xintong Duan, Yutong He, Fahim Tajwar, Ruslan Salakhutdinov, J. Zico Kolter, Jeff G. Schneider

CoRR, June, 2025

Can Large Reasoning Models Self-Train?

Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, Jeff G. Schneider, Andrea Zanette

CoRR, May, 2025

Self-Regulation and Requesting Interventions.

So Yeon Min, Yue Wu, Jimin Sun, Max Kaufmann, Fahim Tajwar, Yonatan Bisk, Ruslan Salakhutdinov

CoRR, February, 2025

State Combinatorial Generalization In Decision Making With Conditional Diffusion Models.

Xintong Duan, Yutong He, Fahim Tajwar, Wentse Chen, Ruslan Salakhutdinov, Jeff G. Schneider

Trans. Mach. Learn. Res., 2025

Reasoning as an Adaptive Defense for Safety.

Taeyoun Kim, Fahim Tajwar, Aditi Raghunathan, Aviral Kumar

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Training a Generally Curious Agent.

Fahim Tajwar, Yiding Jiang, Abitha Thankaraj, Sumaita Sadia Rahman, J. Zico Kolter, Jeff Schneider, Russ Salakhutdinov

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Conservative Prediction via Data-Driven Confidence Minimization.

Caroline Choi, Fahim Tajwar, Yoonho Lee, Huaxiu Yao, Ananya Kumar, Chelsea Finn

Trans. Mach. Learn. Res., 2024

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data.

Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar

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

2023

Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration Bias.

Max Sobol Mark, Archit Sharma, Fahim Tajwar, Rafael Rafailov, Sergey Levine, Chelsea Finn

CoRR, 2023

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts.

Yoonho Lee, Annie S. Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, Chelsea Finn

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning.

Annie Xie, Fahim Tajwar, Archit Sharma, Chelsea Finn

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

Do deep networks transfer invariances across classes?

Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Scalable deep learning to identify brick kilns and aid regulatory capacity.

Jihyeon Janel Lee, Nina R. Brooks, Fahim Tajwar, Marshall Burke, Stefano Ermon, David B. Lobell, Debashish Biswas, Stephen P. Luby

Proc. Natl. Acad. Sci. USA, 2021

No True State-of-the-Art? OOD Detection Methods are Inconsistent across Datasets.

Fahim Tajwar, Ananya Kumar, Sang Michael Xie, Percy Liang

CoRR, 2021