ReflectWorld-MM: Entity-Oriented Memory System for Open-Ended Video Streams

Jul 14, 2026

ReflectWorld-MM is a new memory system for multimodal agents that organizes long-term memory around persistent entities rather than frames, enabling improved tracking of people and objects across open-ended video streams. The system integrates a perception front-end, hierarchical long-term memory (episodic, semantic, procedural), and a real-world implementation. ReflectWorld-MM achieves state-of-the-art accuracy on six long-video and lifelong-memory benchmarks, outperforming existing memory agents and a leading frontier model.

Why it matters: This work advances AI's ability to maintain coherent, entity-centric memory over continuous video, a key step toward persistent, context-aware assistants.

Full story at: arXiv Computer Vision ↗