docs: define speaker-grounded floor experiment plan
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# AMusE: Audio-Visual Benchmark and Alignment Framework for Agentic Multi-Speaker Understanding
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- 作者:Sanjoy Chowdhury 等
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- 发表:CVPR 2026,22998–23009
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- 阅读深度:摘要及官方论文页筛选
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- 核查日期:2026-08-30
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- 来源:[CVF](https://openaccess.thecvf.com/content/CVPR2026/html/Chowdhury_AMusE_Audio-Visual_Benchmark_and_Alignment_Framework_for_Agentic_Multi-Speaker_Understanding_CVPR_2026_paper.html)
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## 摘要与项目关系
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系统评估 MLLM 在多说话人对话中的人物身份追踪、角色保持及音视频事件时序 grounding,报告
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当前通用模型在 agentic multi-speaker understanding 上仍有明显短板。
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该工作不是 wearer floor-entry/yield 预测,也不能作为直接数值基线;它适合与 Multi-speaker
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Attention Alignment 一起支撑“简单加入视觉并不等于获得逐人社会理解”的动机。引用时应把
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其 benchmark/理解任务与本项目 200ms 因果行为预测明确分开。
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