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cs.CV2026
From Content to Knowledge: Lightning Fast Long-Video Understanding with Neural Knowledge Representations
Yuchen Guan, Xiao Li, Zongyu Guo +4
We propose a new paradigm for long video understanding by treating a long video as a Neural Knowledge Representation (NKR). NKR represents video contents neither as a stream of tok…
cs.CV2026
Hierarchical Long Video Understanding with Audiovisual Entity Cohesion and Agentic Search
Xinlei Yin, Xiulian Peng, Xiao Li +2
Long video understanding presents significant challenges for vision-language models due to extremely long context windows. Existing solutions relying on naive chunking strategies w…
cs.CV2025
Bitrate-Controlled Diffusion for Disentangling Motion and Content in Video
Xiao Li, Qi Chen, Xiulian Peng +3
We propose a novel and general framework to disentangle video data into its dynamic motion and static content components. Our proposed method is a self-supervised pipeline with les…