4 papers
MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control
Bin Li, Ruichi Zhang, Han Liang +4
Enabling physics-based humanoids to execute diverse behaviors from high-level textual commands remains a significant challenge. Existing methods typically follow either a two-stage…
SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-based Humanoid Control
Jingyan Zhang, Han Liang, Ruichi Zhang +6
Controlling physics-based humanoids from natural-language instructions is a critical step toward general-purpose embodied agents. However, existing methods remain constrained by a…
InterAgent: Physics-based Multi-agent Command Execution via Diffusion on Interaction Graphs
Bin Li, Ruichi Zhang, Han Liang +6
Humanoid agents are expected to emulate the complex coordination inherent in human social behaviors. However, existing methods are largely confined to single-agent scenarios, overl…
Mojito: LLM-Aided Motion Instructor with Jitter-Reduced Inertial Tokens
Ziwei Shan, Yaoyu He, Chengfeng Zhao +5
Human bodily movements convey critical insights into action intentions and cognitive processes, yet existing multimodal systems primarily focused on understanding human motion via…