4 papers
World-VLA-Loop: Closed-Loop Learning of Video World Model and VLA Policy
Xiaokang Liu, Zechen Bai, Hai Ci +2
Reinforcement learning (RL) can refine Vision-Language-Action (VLA) policies beyond behavior cloning, but real-world RL remains expensive due to extensive rollouts, resets, supervi…
H2R-Grounder: A Paired-Data-Free Paradigm for Translating Human Interaction Videos into Physically Grounded Robot Videos
Hai Ci, Xiaokang Liu, Pei Yang +2
Robots that learn manipulation skills from everyday human videos could acquire broad capabilities without tedious robot data collection. We propose a video-to-video translation fra…
DiffSim: Taming Diffusion Models for Evaluating Visual Similarity
Yiren Song, Xiaokang Liu, Mike Zheng Shou
Diffusion models have fundamentally transformed the field of generative models, making the assessment of similarity between customized model outputs and reference inputs critically…
Anti-Reference: Universal and Immediate Defense Against Reference-Based Generation
Yiren Song, Shengtao Lou, Xiaokang Liu +4
Diffusion models have revolutionized generative modeling with their exceptional ability to produce high-fidelity images. However, misuse of such potent tools can lead to the creati…