EviTrans: Composable State Transitions for Video Reasoning

Video state tracking requires associating events with persistent entities and preserving their history-dependent effects. A fixed interval-level state change can become invalid when earlier records are revised. We present EviTrans, a framework that makes evidence-grounded, composable state transitions the reusable unit of video reasoning. Each interval is represented as an executable function of its entry state and boundary memory, rather than the change realized under one history, preserving state-dependent effects during temporal composition and revision. A typed observation-to-transition interface connects query requirements, visual entity binding, and event decoding to executable updates, while retaining evidence references and unresolved information. Integrating this representation with a persistent segment tree and deterministic query programs enables compatible questions to share an executable history and compiled records to be revised while preserving earlier versions. On VSTAT's 834 videos and 1,500 questions, the frozen, offline configuration achieves an overall score of 51.11, exceeding the matched direct video question answering baseline by 13.58 points, with unavailable inputs retained as failures. In backend diagnostics on 211 videos retaining 33 versions, persistent maintenance reduces edit-to-answer latency by 22.2% and retained memory by 52.1% relative to blocked sequential execution, while historical queries are slower under the measured caching policies.