2 papers
cs.CV2026
VideoThinker: Building Agentic VideoLLMs with LLM-Guided Tool Reasoning
Chenglin Li, Qianglong Chen, Feng Han +6
Long-form video understanding remains a fundamental challenge for current Video Large Language Models. Most existing models rely on static reasoning over uniformly sampled frames,…
cs.CV2026
VideoPro: Adaptive Program Reasoning for Long Video Understanding
Chenglin Li, Feng Han, Yikun Wang +9
Large language models (LLMs) have shown promise in generating program workflows for visual tasks. However, previous approaches often rely on closed-source models, lack systematic r…