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cs.RO2026
Turning Video Models into Generalist Robot Policies
Sizhe Lester Li, Evan Kim, Xingjian Bai +4
Video generative models have emerged as a promising robotics backbone, capable of generating videos that depict the completion of complex tasks across embodiments and environments.…
cs.CV2026
End-to-End Training for Unified Tokenization and Latent Denoising
Shivam Duggal, Xingjian Bai, Zongze Wu +5
Latent diffusion models (LDMs) enable high-fidelity synthesis by operating in learned latent spaces. However, training state-of-the-art LDMs requires complex staging: a tokenizer m…
cs.CV2026
Causality in Video Diffusers is Separable from Denoising
Xingjian Bai, Guande He, Zhengqi Li +3
Causality -- referring to temporal, uni-directional cause-effect relationships between components -- underlies many complex generative processes, including videos, language, and ro…