English(EN) Realtime-Bench: Can Frontier Models Solve Real-time Interactive Problems?

新的Realtime-Bench测试AI模型在时间约束下的行动能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-16 04:00

一项名为Realtime-Bench的新基准已被开发出来，用于评估前沿AI模型在实时交互环境中执行任务的能力。该基准包含动态任务，其中延迟的行动会降低成功率。使用Realtime-Bench进行的实验表明，即使是最好的模型，在考虑实际推理延迟的“Wall Clock”设置下，成功率也仅为44%。该基准还引入了“Paused Clock”和“Token Clock”，以区分服务延迟和模型固有的实时流式传输能力，揭示了在时间压力下决策质量与及时执行之间的权衡。 AI

影响强调了AI模型在实时交互任务中的挑战，并为提高时间感知和自适应推理能力指明了方向。

排序理由该条目是一篇研究论文，介绍了一个用于评估AI模型的新基准。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Jingyu Tang, Xu Yang, Zhehao Zhang, Zheng Wang, Qi Cheng, Haozhe Zhao, Manling Li, Wenxuan Li, Xide Xia, Jiaxin Pei · 2026-10-16 04:00

Realtime-Bench：前沿模型能否解决实时交互问题？

arXiv:2610.22155v1 Announce Type: new Abstract: Real-time interaction requires agents to perceive evolving environments and act under temporal constraints, yet existing evaluations of real-time streaming models focus on conversational quality and streaming perception, leaving eff…

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报道来源 [1]

Realtime-Bench：前沿模型能否解决实时交互问题？

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