科學發現的基礎模型：從範式增強到範式轉變

摘要

基础模型（FMs），如GPT-4和AlphaFold，正在重塑科学研究的格局。除了加速假设生成、实验设计和结果解释等任务外，它们还引发了一个更为根本的问题：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？在本文中，我们主张FMs正在催化向新科学范式的过渡。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，FMs在传统范式内增强工作流程；（2）人机混合共创，FMs成为问题构建、推理和发现中的积极合作者；（3）自主科学发现，FMs作为独立代理，能够在最少人为干预的情况下生成新的科学知识。通过这一视角，我们回顾了FMs在现有科学范式中的当前应用和新兴能力。我们进一步识别了FMs赋能科学发现的风险和未来方向。本立场文件旨在支持科学界理解FMs的变革性作用，并促进对科学发现未来的反思。我们的项目可在https://github.com/usail-hkust/Awesome-Foundation-Models-for-Scientific-Discovery获取。

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.

科學發現的基礎模型：從範式增強到範式轉變

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

摘要

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