ViSAGE: Self-Correcting Memory Framework for Long-Form Video Understanding

ViSAGE, a new multimodal agentic memory framework, has been developed by researchers to tackle issues related to long-form video comprehension. This innovative framework creates self-correcting, entity-focused memories that facilitate consistent reasoning about entities and temporal grounding in extended environments. Traditional agentic memory techniques often overlook detailed identity signals due to aggressive compression and segment-based processing, heavily depending on vector similarity retrieval. This reliance can result in confusion between entities, propagation of errors, and inaccurate responses. ViSAGE enhances entity identity through cross-modal binding across extended time periods, employs bidirectional memory refinement to relay delayed identity information, and introduces multi-agent cross-verification for evaluating retrieval accuracy. The research paper can be found on arXiv under identifier 2607.28678.