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新方法提升MLLM处理长视频的效率 · 追踪3个来源

作者 PulseAugur 编辑部 · [3 个来源] ·

研究人员正在开发新方法，以提高多模态大语言模型（MLLM）处理长视频时的效率和准确性。VideoMM提出了一种自适应方法，将语义过滤与详细推理分开，在将相关区域投影到高保真标记之前，使用成本效益高的代理进行初步选择。CodecSight利用视频编解码器信号来指导推理，在无需模型特定训练的情况下减少计算并提高流媒体能力。Video-HolmesV2引入了一个基准和框架，强调深度视听耦合，并要求模型用精确的时空证据来证明答案，从而解决了以视觉为中心的评估和低效的上下文处理的局限性。 AI

影响 这些进展旨在使MLLM在分析长视频内容方面更加实用，有可能为内容摘要、搜索和分析等新应用带来可能。

排序理由 三篇研究论文介绍了使用多模态大语言模型处理长视频的新方法和基准。

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新方法提升MLLM处理长视频的效率 · 追踪3个来源

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三篇研究论文介绍了使用多模态大语言模型处理长视频的新方法和基准。
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报道来源 [3]

  1. arXiv cs.AI TIER_1 Español(ES) · Haoyu Guo, Yuan Feng, Junlin Lv, Mingjun Xiao, S Kevin Zhou, Xike Xie ·

    VideoMM：高效视频多模态大语言模型 (MLLM) 的自适应宏观-微观推理

    arXiv:2609.16722v1 Announce Type: new Abstract: Scaling Multimodal Large Language Models (MLLMs) to long-form video understanding is bottlenecked by the explosion of visual tokens, which saturates context windows and incurs prohibitive costs. Current solutions predominantly rely …

  2. arXiv cs.LG TIER_1 English(EN) · Yulin Zou, Wenyan Chen, Yan Chen, Anya Rajan, JooYoung Park, Shivaraman Nitin, Luo Tao, Francisco Romero, Dmitrii Ustiugov ·

    CodecSight：利用视频编解码器信号实现高效流式VLM推理

    arXiv:2604.06036v4 Announce Type: replace-cross Abstract: Continuous inference over concurrent video streams imposes substantial compute and memory demands on vision-language model (VLM) serving. Streaming inference uses sliding windows to maintain a bounded context of recent vid…

  3. arXiv cs.CV TIER_1 English(EN) · Zhaoyang Wei, Zipeng Wang, Yushe Cao, Chenhui Qiang, Shuaibing Cheng, Xuesong Yang, Sen Nie, Bowen Jiang, Wenchao Ding, Yanchao Hao, Zheng Wei, Xuehui Yu, Zhenjun Han ·

    Video-HolmesV2：多模态大模型能否在长视频中利用时空音视频证据进行推理？

    arXiv:2609.17248v1 Announce Type: new Abstract: Multimodal Large Language Models have demonstrated impressive video understanding, yet their ability to reason over long-form narratives is often masked by visual-centric evaluations and inefficient context processing. Existing benc…

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