对推理法学硕士的理解和监控

IF 29.8 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Nature Machine Intelligence Pub Date : 2026-10-19 DOI:10.1038/s42256-026-01333-6

引用次数: 0

摘要

前沿法学硕士被训练以一步一步的方式解决问题，用人类可理解的语言生成推理文本。然而，这些推理令牌并不能准确解释llm的内部计算，这给可监控性带来了挑战。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Towards understanding and monitorability of reasoning LLMs

Frontier LLMs are trained to solve problems in a step-by-step way, generating reasoning text in human-understandable language. However, these reasoning tokens are not accurate explanations of LLMs’ internal computations, raising challenges for monitorability.

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来源期刊

Nature Machine Intelligence Multiple-

CiteScore

36.90

自引率

2.10%

发文量

127

期刊介绍： Nature Machine Intelligence is a distinguished publication that presents original research and reviews on various topics in machine learning, robotics, and AI. Our focus extends beyond these fields, exploring their profound impact on other scientific disciplines, as well as societal and industrial aspects. We recognize limitless possibilities wherein machine intelligence can augment human capabilities and knowledge in domains like scientific exploration, healthcare, medical diagnostics, and the creation of safe and sustainable cities, transportation, and agriculture. Simultaneously, we acknowledge the emergence of ethical, social, and legal concerns due to the rapid pace of advancements. To foster interdisciplinary discussions on these far-reaching implications, Nature Machine Intelligence serves as a platform for dialogue facilitated through Comments, News Features, News & Views articles, and Correspondence. Our goal is to encourage a comprehensive examination of these subjects. Similar to all Nature-branded journals, Nature Machine Intelligence operates under the guidance of a team of skilled editors. We adhere to a fair and rigorous peer-review process, ensuring high standards of copy-editing and production, swift publication, and editorial independence.