254 citations · 557 across the 16 of their papers we have counts for
16 papers
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…
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…
MaskedMimic: Unified Physics-Based Character Control Through Masked Motion Inpainting
Chen Tessler, Yunrong Guo, Ofir Nabati +2
Crafting a single, versatile physics-based controller that can breathe life into interactive characters across a wide spectrum of scenarios represents an exciting frontier in chara…
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…
PlaMo: Plan and Move in Rich 3D Physical Environments
Assaf Hallak, Gal Dalal, Chen Tessler +3
Controlling humanoids in complex physically simulated worlds is a long-standing challenge with numerous applications in gaming, simulation, and visual content creation. In our setu…
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters
Chen Tessler, Yoni Kasten, Yunrong Guo +3
In this work, we present Conditional Adversarial Latent Models (CALM), an approach for generating diverse and directable behaviors for user-controlled interactive virtual character…