3 papers
cs.LG2026
Task Tokens: A Flexible Approach to Adapting Behavior Foundation Models
Ron Vainshtein, Zohar Rimon, Shie Mannor +1
Recent advancements in imitation learning have led to transformer-based behavior foundation models (BFMs) that enable multi-modal, human-like control for humanoid agents. While exc…
cs.LG2025
Gradient Boosting Reinforcement Learning
Benjamin Fuhrer, Chen Tessler, Gal Dalal
We present Gradient Boosting Reinforcement Learning (GBRL), a framework that adapts the strengths of gradient boosting trees (GBT) to reinforcement learning (RL) tasks. While neura…
cs.LG2024
Improving Inverse Folding for Peptide Design with Diversity-regularized Direct Preference Optimization
Ryan Park, Darren J. Hsu, C. Brian Roland +5
Inverse folding models play an important role in structure-based design by predicting amino acid sequences that fold into desired reference structures. Models like ProteinMPNN, a m…