SurgCouple: Coupling Global Context with Local Cues via Chain of Spatio-temporal Evidence for Surgical Video Understanding

Similar surgical phases and instrument configurations can involve distinct instrument–tissue interactions, so global context alone cannot discriminate local events. Existing multimodal LLMs, however, lack a mechanism for selectively attending to sparse, spatial-temporal cues. We introduce **SurgCouple**, the first surgical video reasoning framework to **couple global context with hypothesis-guided spatial-temporal evidence discovery**. An Evidence Chain progressively discovers temporal, spatial, and fine-grained evidence, with intermediate reasoning states providing hypothesis-guided feedback to the latter two stages to focus on the informative regions. A Reasoning Chain maintains an evolving interpretation of the surgical event, refining the hypothesis space as evidence accumulates. A Consistency Verifier ensures that local judgments remain grounded in the evidence actually selected and coherent across stages. With a frozen Qwen3-VL-8B, SurgCouple achieves 89.31% final-answer accuracy and a 58.92% valid chain rate, surpassing 81.94% and 34.01% for Qwen3-VL-8B, and 88.92% and 52.63% for GPT-5.5.