arXiv:2510.15280cs.LGcs.AI2025-10NeurIPS被引 9

基础模型正推动科学发现从辅助到自主的范式转变。

Foundation Models for Scientific Discovery: From Paradigm Enhancement to Paradigm Transition

  • 提出三阶段演进框架:融合、人机共创、自主发现。
  • 揭示基础模型从工具到独立科研主体的潜力。
  • 适合关注AI驱动科研变革的研究者参考。

基础模型(FMs),如GPT-4和AlphaFold,正在重塑科学研究格局。它们不仅加速假设生成、实验设计与结果解读,更引发根本性问题:FMs是增强现有科学方法,还是在重新定义科学实践方式?本文认为,FMs正催化新科学范式的形成。我们提出三阶段框架:(1) 元科学整合,即在传统范式内提升工作流效率;(2) 人机协同创造,即FMs参与问题构建、推理与发现;(3) 自主科学发现,即FMs作为独立智能体,在极少人类干预下生成新知识。基于此视角,我们综述了当前应用与新兴能力,并识别潜在风险与未来方向。本文旨在帮助科学界理解FMs的变革作用,推动对科学发现未来的深入思考。项目地址:https://github.com/usail-hkust/Awesome-Foundation-Models-for-Scientific-Discovery。

原文摘要 · Abstract (English)

Foundation models (FMs), such as GPT-4 and AlphaFold, are reshaping the landscape of scientific research. Beyond accelerating tasks such as hypothesis generation, experimental design, and result interpretation, they prompt a more fundamental question: Are FMs merely enhancing existing scientific methodologies, or are they redefining the way science is conducted? In this paper, we argue that FMs are catalyzing a transition toward a new scientific paradigm. We introduce a three-stage framework to describe this evolution: (1) Meta-Scientific Integration, where FMs enhance workflows within traditional paradigms; (2) Hybrid Human-AI Co-Creation, where FMs become active collaborators in problem formulation, reasoning, and discovery; and (3) Autonomous Scientific Discovery, where FMs operate as independent agents capable of generating new scientific knowledge with minimal human intervention. Through this lens, we review current applications and emerging capabilities of FMs across existing scientific paradigms. We further identify risks and future directions for FM-enabled scientific discovery. This position paper aims to support the scientific community in understanding the transformative role of FMs and to foster reflection on the future of scientific discovery. Our project is available at https://github.com/usail-hkust/Awesome-Foundation-Models-for-Scientific-Discovery.

基础模型科学发现范式转移

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