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English(EN) EventMemAgent: Hierarchical Event-Centric Memory for Online Video Understanding with Adaptive Tool Use

EventMemAgent框架通过分层记忆增强在线视频理解能力

研究人员推出了一种新颖的框架EventMemAgent,专为在线视频理解而设计,以应对多模态大语言模型(MLLMs)中有限上下文窗口的挑战。该代理框架利用分层记忆系统,包括用于事件边界检测和动态缓冲区采样的短期记忆组件,以及用于结构化存档过去观察的长时记忆。它还集成了多粒度感知工具包和代理强化学习,以实现推理和工具使用策略的端到端学习。 AI

影响 该框架有望改进AI系统处理和推理连续视频流的方式,可能对监控、内容审核和自主系统等应用产生影响。

排序理由 该条目是一篇研究论文,详细介绍了一种新的在线视频理解框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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EventMemAgent框架通过分层记忆增强在线视频理解能力

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该条目是一篇研究论文,详细介绍了一种新的在线视频理解框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Siwei Wen, Zhangcheng Wang, Xingjian Zhang, Lei Huang, Wenjun Wu ·

    EventMemAgent:用于在线视频理解和自适应工具使用的分层事件中心记忆

    arXiv:2602.15329v2 Announce Type: replace Abstract: Online video understanding requires models to perform continuous perception and long-range reasoning within potentially infinite visual streams. Its fundamental challenge lies in the conflict between the unbounded nature of stre…