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English(EN) New paper from Stanford, Together AI, UIUC, and Meta introduces Hybrid Reasoning Agents. These AI models think mostly in a hidden internal way (faster and cheaper), and only use normal text when they need tools or give the final answer.

混合推理代理提高 AI 性能和效率

来自斯坦福大学、Together AI、伊利诺伊大学厄巴纳-香槟分校和 Meta 的研究人员推出了一种新颖的 AI 架构——混合推理代理。这些代理主要通过更快、更具成本效益的内部推理过程运行,仅在必要时才与外部工具交互或生成最终输出。与传统模型相比,这种方法在性能上有了显著提升,在各种基准测试中得分提高了约 10%,同时使用的 token 数量减少了一半,运行速度提高了一倍。 AI

影响 这种新架构通过优化内部推理过程,有望带来更高效、更具成本效益的 AI 系统。

排序理由 该集群描述了一篇介绍新颖 AI 架构的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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混合推理代理提高 AI 性能和效率

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该集群描述了一篇介绍新颖 AI 架构的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/R_Duncan ·

    斯坦福大学、Together AI、UIUC 和 Meta 的新论文介绍了混合推理代理。这些 AI 模型主要以隐藏的内部方式进行思考(更快、更便宜),并且仅在需要工具或给出最终答案时才使用普通文本。

    <!-- SC_OFF --><div class="md"><p>On many tests (math, science, medicine, etc.), they score about 10% higher, use half the tokens, run twice as fast, and cost much less than regular models.</p> <p>mod here, paper link: <a href="https://arxiv.org/abs/2610.18861">[2610.18861] Hybri…