English(EN) Can LLMs Discover Scientific Laws in Real and Parallel Worlds?

新基准SCILAWS-BENCH测试大型语言模型发现科学定律的能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-02 04:00

研究人员推出了SCILAWS-BENCH，这是一个旨在评估大型语言模型（LLMs）发现科学定律能力的新基准。该基准包含118个问题，源自六个学科的科学论文，使用了大约800万个数据点。它在两种设置下呈现问题：SCILAWS-REAL，评估从固定现实世界观测中发现定律的能力；以及SCILAWS-PARALLEL，涉及模型主动查询合成世界以恢复隐藏定律。研究发现，预测拟合可能与科学有效性不同，模型记忆会影响它们超越现有公式的能力。 AI

影响该基准旨在提供对人工智能科学发现能力更稳健的评估，超越合成或熟悉的问题。

排序理由该集群包含一篇介绍用于评估人工智能能力的新基准的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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Newsworthiness bucket: Tool; 该集群包含一篇介绍用于评估人工智能能力的新基准的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Yiming Huang, Ziche Liu, Zhuohang Wu, Yiqian Wang, Junxia Cui, Xinkai Zou, Linjun Mao, Nan Huang, Naicheng Yu, Kaijie Zhu, Yue Ma, Kun Zhou, Letian Peng, Jingbo Shang · 2026-09-02 04:00

大型语言模型能否在真实和并行世界中发现科学定律？

arXiv:2609.01552v1 Announce Type: new Abstract: Scientific equation discovery has long been central to scientific progress, proceeding through iterative cycles of hypothesis generation, observational testing, and refinement under scientific constraints. As LLM capabilities advanc…

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报道来源 [1]

大型语言模型能否在真实和并行世界中发现科学定律？

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