13 citations · 39 across the 13 of their papers we have counts for
3 papers · 1 filter
PhysWAM: Physically Consistent World Action Model for Autonomous Driving
Dhruv Parikh, Fengcheng Yu, Quankai Gao +11
World-action models (WAMs) jointly predict how a scene will evolve and how an agent should act, however joint generation alone does not necessarily impose a shared geometric constr…
Residual Denoising Enables Sample-Efficient Multi-Agent Coordination on Demand
Dayi Dong, Maulik Bhatt, Aayushi Shrivastava +2
Pretrained robot policies offer strong manipulation skills but are typically limited to single-agent settings, where a robot acts in isolation. In this work, we study how to adapt…
DriveReferee: Geometric Safety Verdicts Need Not Be Learned for Driving World-Action Models
Fengcheng Yu, Dhruv Parikh, Junjie Ye +5
Generative world-action models (WAMs) jointly generate future video and vehicle actions, while their action branches remain primarily optimized by expert imitation. Yet imitation p…