RL’s Razor: Why Online Reinforcement Learning Forgets Less
Idan Shenfeld, Jyothish Pari, Pulkit Agrawal
Published in Arxiv Preprint, 2025
Publications
Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty
Mehul Damani, Isha Puri, Stewart Slocum, Idan Shenfeld, Leshem Choshen, Yoon Kim, Jacob Andreas
Published in Arxiv Preprint, 2025
Language Model Personalization via Reward Factorization
Idan Shenfeld, Felix Faltings, Pulkit Agrawal, Aldo Pacchiano
Published in COLM, 2025
Learning How Hard to Think: Input-Adaptive Allocation of LM Computation
Mehul Damani, Idan Shenfeld, Andi Peng, Andreea Bobu, Jacob Andreas
Published in ICLR, 2025
The Future of Open Human Feedback
Shachar Don-Yehiya, Ben Burtenshaw,... Idan Shenfeld ..., Leshem Choshen
Published in Nature Machine Intelligence, 2025
Value Augmented Sampling for Language Model Alignment and Personalization
Idan Shenfeld, Seungwook Han, Akash Srivastava, Yoon Kim, Pulkit Agrawal
Published in ICLR 2024 Workshop on Reliable and Responsible Foundation Models (**Oral Talk**), 2024
Curiosity-driven Red-teaming for Large Language Models
Zhang-Wei Hong, Idan Shenfeld, Tsun-Hsuan Wang, Yung-Sung Chuang, Aldo Pareja, James R. Glass, Akash Srivastava, Pulkit Agrawal
Published in ICLR, 2024
TGRL: An Algorithm for Teacher Guided Reinforcement Learning
Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, and Pulkit Agrawal
Published in ICML, 2023
Selected for Oral Presentation at 2023 ICLR RRL Workshop.
Offline Meta Reinforcement Learning - Identifiability Challenges and Effective Data Collection Strategies
Ron Dorfman, Idan Shenfeld, and Aviv Tamar
Published in NeurIPS, 2021