研究人员推出了 OmniPro 和 VideoOdyssey 两个新基准，旨在评估全模态大语言模型理解长而复杂视频内容的能力。OmniPro 专注于主动式流媒体视频理解，评估模型从视听流中决定何时以及说什么的能力，包含跨越不同任务的 2,700 个经人工验证的样本。VideoOdyssey 针对超长上下文视频理解，包含极长的视频（平均 109 分钟），并评估在长时间内的连续推理和记忆保持能力。这两个基准都突显了当前模型在长视域鲁棒性、音频利用以及细粒度感知方面的局限性，尤其是在处理非语音音频时。 AI
影响 这些基准将推动能够理解复杂、长格式视频内容的人工智能模型的发展，这对于监控、内容分析和自主系统等应用至关重要。
排序理由 两篇新研究论文介绍了用于评估人工智能模型的基准。
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OmniPro is introduced as the first benchmark for evaluating omni-modal large language models' proactive streaming video understanding, featuring diverse tasks and dual-mode evaluation protocols.
arXiv:2605.25621v1 Announce Type: new Abstract: While streaming omni-video understanding demands continuous perception and proactive, real-time interaction, this crucial area remains largely under-explored. Current omni-modal methods are inherently designed for offline settings, …
While streaming omni-video understanding demands continuous perception and proactive, real-time interaction, this crucial area remains largely under-explored. Current omni-modal methods are inherently designed for offline settings, limiting their applicability in streaming scenar…
arXiv:2605.22907v1 Announce Type: new Abstract: Real-world long video understanding requires models to perform continuous tracking, information integration and memory retention over massive temporal spans within extreme video durations. Mastering this intense cognitive load const…