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cs.RO2025

Commanding Humanoid by Free-form Language: A Large Language Action Model with Unified Motion Vocabulary

Zhirui Liu, Kaiyang Ji, Ke Yang +4

Enabling humanoid robots to follow free-form natural language commands is a critical step toward seamless human-robot interaction and general-purpose embodied AI. However, existing…

cs.CV2025

Towards Immersive Human-X Interaction: A Real-Time Framework for Physically Plausible Motion Synthesis

Kaiyang Ji, Ye Shi, Zichen Jin +5

Real-time synthesis of physically plausible human interactions remains a critical challenge for immersive VR/AR systems and humanoid robotics. While existing methods demonstrate pr…

cs.RO2025

DreamPolicy: A Unified World-model Policy for Scalable Humanoid Locomotion

Yahao Fan, Tianxiang Gui, Kaiyang Ji +8

Achieving versatile humanoid locomotion with a single policy presents a critical scalability challenge. Prevailing methods often rely on distilling multiple terrain-specific teache…

cs.CV2025

Human-Object Interaction via Automatically Designed VLM-Guided Motion Policy

Zekai Deng, Ye Shi, Kaiyang Ji +3

Human-object interaction (HOI) synthesis is crucial for applications in animation, simulation, and robotics. However, existing approaches either rely on expensive motion capture da…

cs.CV2025

ARFlow: Human Action-Reaction Flow Matching with Physical Guidance

Wentao Jiang, Jingya Wang, Kaiyang Ji +3

Human action-reaction synthesis, a fundamental challenge in modeling causal human interactions, plays a critical role in applications ranging from virtual reality to social robotic…