封闭模型阻碍科学推断，开放程度影响研究可信度。
How Open Must Language Models be to Enable Reliable Scientific Inference?
- 评估模型开放性对科学推断可靠性的影响
- 指出封闭模型普遍不适合作为科研工具
- 建议研究中明确说明模型选择理由与风险缓解措施
本研究探讨模型开放程度如何影响基于其开展的研究的科学推断可靠性。我们分析了模型构建与部署信息受限对可信赖推断的威胁，认为当前大多数封闭模型在科学用途上存在根本缺陷，尽管少数情况例外。文章讨论了这些问题的解决或缓解路径，建议在科研中系统识别潜在推断风险，并提供模型选择的具体理由及应对措施，以提升研究透明度与可信度。
原文摘要 · Abstract (English)
How does the extent to which a model is open or closed impact the scientific inferences that can be drawn from research that involves it? In this paper, we analyze how restrictions on information about model construction and deployment threaten reliable inference. We argue that current closed models are generally ill-suited for scientific purposes, with some notable exceptions, and discuss ways in which the issues they present to reliable inference can be resolved or mitigated. We recommend that when models are used in research, potential threats to inference should be systematically identified along with the steps taken to mitigate them, and that specific justifications for model selection should be provided.
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