- OmniMem-Lens uses dual-stream visual and auditory trajectories to enable event-based rather than second-based video memory for agents.
- Compared to traditional fixed-window slicing, the new method improves recall accuracy by up to 45.7% and reduces Q&A latency by up to 97%.
- The feature is officially released and open-sourced in openJiuwen AgentMemory version 0.2.0.
AI CURATED HOT STORY · 11/3/2026
openJiuwen Launches OmniMem-Lens to Boost Long Video Memory Accuracy
The release of openJiuwen AgentMemory 0.2.0 introduces OmniMem-Lens, a multimodal memory capability that marks a significant breakthrough in AI agent long video understanding. By leveraging visual and auditory dual-stream trajectories, the solution segments video memories based on real events rather than fixed time windows, effectively resolving issues of evidence fragmentation and key information loss inherent in traditional methods.
Cross-verified reports highlight that OmniMem-Lens mimics human cognitive mechanisms by remembering videos 'by event' instead of 'by second.' Compared to conventional fixed-window slicing, this new architecture optimizes retrieval efficiency while preserving semantic integrity. Benchmark tests show that recall accuracy improves by up to 45.7%, and online Q&A latency decreases by as much as 97%, significantly enhancing the agent's real-time response capabilities for complex video tasks.
This open-source feature profoundly impacts the developer ecosystem. It lowers the barrier to building agents with deep video comprehension and provides a standardized solution for industries requiring efficient processing of massive audiovisual data, potentially accelerating the adoption of AI agents in multimodal interaction scenarios.
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- OmniMem-Lens uses dual visual-auditory streams to segment video memory by events rather than seconds
- Addresses evidence fragmentation and key information drowning caused by fixed time windows
- Benchmarks show up to 45.7% improvement in recall accuracy and 97% reduction in Q&A latency