科学发现的基础模型：从范式增强到范式转变

摘要

诸如GPT-4和AlphaFold等基础模型（FMs）正在重塑科学研究的格局。它们不仅加速了假设生成、实验设计和结果解读等任务，更引发了一个根本性的问题：FMs仅仅是增强了现有的科学方法论，还是在重新定义科学实践的方式？本文主张，FMs正推动科学向新范式的转变。我们引入了一个三阶段框架来描述这一演变：（1）元科学整合阶段，FMs在传统范式内优化工作流程；（2）人机共创混合阶段，FMs成为问题构建、推理与发现过程中的积极合作者；（3）自主科学发现阶段，FMs作为独立主体，能够在极少人为干预下生成新的科学知识。通过这一视角，我们审视了FMs在现有科学范式中的当前应用与新兴能力，并进一步识别了基于FMs的科学发现所面临的风险与未来方向。本立场文件旨在帮助科学界理解FMs的变革性作用，并促进对科学发现未来的深入思考。我们的项目详情可见于https://github.com/usail-hkust/Awesome-Foundation-Models-for-Scientific-Discovery。

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.

科学发现的基础模型：从范式增强到范式转变

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

摘要

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