English(EN) Adaptive Stopping of Streamed Reasoning for Language Model Agents

新的StreamStop方法优化语言模型代理推理效率

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-21 04:00

研究人员开发了一种名为StreamStop的新方法，以优化语言模型代理的推理过程。该技术通过分析部分和完整推理轨迹之间的一致性来离线学习特定模型的停止策略。StreamStop允许代理在无需访问模型内部信号的情况下决定何时停止推理，仅使用一个轻量级的停止头。在WebShop和ScienceWorld等基准测试上的评估表明，StreamStop在保持相似的任务成功率的同时，显著减少了推理令牌的使用量，例如，在WebShop上使用Qwen3.8-27B时，令牌使用量减少了42%。 AI

影响通过优化推理步骤，降低了语言模型代理的计算成本。

排序理由这是一篇详细介绍语言模型代理新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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arXiv cs.CL TIER_1 English(EN) · JunHyeok Oh, Byung-Jun Lee · 2026-10-21 04:00

语言模型代理的流式推理自适应停止

arXiv:2610.27981v1 Announce Type: new Abstract: Reasoning-enabled language model agents can incur substantial computation before acting, although the reasoning needed varies across decisions. Existing stopping signals, such as confidence and intermediate-answer stability, can var…

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语言模型代理的流式推理自适应停止

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