研究发现论文中AI使用披露与科研实际需求脱节，需改进政策设计。
Expectations and Practices around AI Disclosure in CS Research
- 按任务必要性分类披露，高设计参与度任务更需披露。
- 13867份投稿显示写作辅助常被披露但实际被认为不必要。
- 建议采用标准化模板，匹配研究人员真实期待。
随着生成式AI在科研流程中日益普及，多个出版平台出台了AI使用披露政策。本文首先分析顶会披露政策，发现其普遍模糊不清；通过针对109名计算机科学家的调查，揭示研究人员认为在研究设计环节及人类参与度低的任务中，披露最为必要；进一步分析EMNLP 2025和ICLR 2026共13867条披露声明发现，实际披露内容与研究人员预期存在显著偏差——例如写作辅助虽常被披露，却被认为必要性较低。研究据此提出建议：应根据任务类型划分披露必要性等级，并采用标准化模板以更好传递关键信息。
原文摘要 · Abstract (English)
As generative AI tools find increasing use in research workflows, ongoing debates on their impact, appropriateness and responsible use have led policymakers to enact policies to disclose AI use at multiple publishing venues. However, are current AI disclosure policies and practices reflective of their purpose? In this work, we first investigate disclosure policies of top computer science venues and find that despite their prevalence, they remain highly under-specified. Secondly, through a survey of computer science researchers (N=$109$), we characterize the necessity of disclosures across different research tasks and levels of human involvement. We learn that researchers find disclosures most necessary for tasks involving research design, and for tasks when the human involvement is low. We also compile expectations that researchers have about the information to be conveyed in AI disclosure statements. Lastly, through an analysis of $13867$ disclosure statements from EMNLP $2025$ and ICLR $2026$, we reveal a large disconnect between these expectations and AI disclosures in practice---a prime example being writing assistance which is deemed less necessary but is frequently disclosed. We conclude with recommendations to align AI disclosure policies and practices with expectations, suggesting a categorization of research tasks by perceived necessity and a boilerplate template capturing expected details.
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