5 papers
Function-Space Diffusion for Motion Planning
Zinuo Chang, Yipu Chen, Byoungwoo Park +2
Diffusion-based motion planners have demonstrated strong performance in generating diverse and high-quality robot trajectories in cluttered environments with multiple feasible solu…
VQActFlow: Vector-Quantized Action Mode Steering for Multi-Task Robot Manipulation
Zhigen Zhao, Mark Leggiero, Yipu Chen +5
Multi-task robot manipulation policies are challenging to learn from demonstration because traditionally a single network must select among qualitatively different action modes fro…
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +306
Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…
ACWM-Phys: Investigating Generalized Physical Interaction in Action-Conditioned Video World Models
Haotian Xue, Yipu Chen, Liqian Ma +4
Action-conditioned world models (ACWMs) have shown strong promise for video prediction and decision-making. However, existing benchmarks are largely restricted to egocentric naviga…
REFINE-DP: Diffusion Policy Fine-tuning for Humanoid Loco-manipulation via Reinforcement Learning
Zhaoyuan Gu, Yipu Chen, Zimeng Chai +12
Humanoid loco-manipulation requires coordinated task-space motion planning with stable loco-manipulation command tracking under complex robot-environment dynamics and long-horizon…