Aligning Language Models From User Interactions
Thomas Kleine Buening, Jonas Hübotter, Barna Pásztor, Idan Shenfeld, Giorgia Ramponi, Andreas Krause
Published in Arxiv Preprint, 2026
Publications
Reaching Beyond the Mode: RL for Distributional Reasoning in Language Models
Isha Puri, Mehul Damani, Idan Shenfeld, Marzyeh Ghassemi, Jacob Andreas, Yoon Kim
Published in ICML, 2026
Self-Distillation Enables Continual Learning
Idan Shenfeld, Mehul Damani, Jonas Hübotter, Pulkit Agrawal
Published in ICML, 2026
Best Paper Award at Lifelong Agents Workshop, ICLR 2026
Reinforcement Learning via Self-Distillation
Jonas Hübotter, Frederike Lübeck,... Idan Shenfeld,... Andreas Krause
Published in ICML, 2026
RL’s Razor: Why Online Reinforcement Learning Forgets Less
Idan Shenfeld, Jyothish Pari, Pulkit Agrawal
Published in ICLR, 2026
Outstanding Paper Award at the CCFM Workshop, NeurIPS 2025
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 ICLR, 2026
Best-of-n through the Smoothing Lens: KL Divergence and Regret Analysis
Gholamali Aminian, Idan Shenfeld, Amir Asadi, Ahmad Beirami, Youssef Mroueh
Published in ICLR, 2026
Language Model Personalization via Reward Factorization
Idan Shenfeld, Felix Faltings, Pulkit Agrawal, Aldo Pacchiano
Published in COLM, 2025
KL-Regularized RLHF with Multiple Reference Models: Exact Solutions and Sample Complexity
Gholamali Aminian, Amir Asadi, Idan Shenfeld, Youssef Mroueh
Published in NeurIPS, 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 Oral presentation at Workshop on Reliable and Responsible Foundation Models, ICLR 2024, 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
From Imitation to Refinement: Residual RL for Precise Visual Assembly
Lars Lien Ankile, Anthony Simeonov, Idan Shenfeld, Marcel Torne Villasevil, Pulkit Agrawal
Published in ICRA, 2025
Juicer: Data-efficient Imitation Learning for Robotic Assembly
Lars Ankile, Anthony Simeonov, Idan Shenfeld, Pulkit Agrawal
Published in IROS, 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