StreamOPD: A Post-Training Recipe with Spatio-Temporal Cue Gating for Streaming Video Understanding

StreamOPD improves streaming video understanding by applying on-policy distillation (OPD) in thinking mode to enable stable post-training. This recipe uses dense token-level supervision and verifiable streaming data to optimize models for instruct-mode deployment without requiring additional inference-time memory or retrieval mechanisms.