Keqian Li

When and Where to Look: Adaptive Visual Evidence Scheduling for Efficient Long Video Understanding

Efficient long-video understanding requires vision--language models (VLMs) to reason over a small number of frames selected as sparse visual evidence. Existing relevance-based methods rely on static one-shot selection with fixed frame budgets and candidate pools, while agent-based schedulers achieve adaptivity through...