RINI：看到先验是不够的
RINI: Seeing the Prior Is Not Enough
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中文总结 AI 辅助
本研究提出RINI方法，通过审计贡献声明和检查剩余区别来纠正研究提案中的无依据新颖性，实验表明其修复成功率显著高于基线方法。
中文摘要 AI 辅助
一份研究提案可以正确描述一个已有机制，却声称是首次引入该机制。我们研究提供早期论文是否能纠正此类贡献声明。三项受控实验比较了使用带有贡献的先验和同主题对照生成的提案。提供先验并未带来无依据新颖性的总体显著减少。对175份可解释的暴露提案的人工分析发现，137份识别了先验的相关性，但61份正确归属了已有贡献。在71个提出的剩余区别中，37个被同一先验所覆盖。我们引入了研究想法新颖性检查（RINI），它根据证据审计贡献声明，检查剩余区别，并应用局部修订。五名人工标注者评估了三种方法下的1,080对原始-修订对。在同样被判定需要纠正的240份原始提案中，成功修复率对于自我修订为11.7%，对于检索-修订为39.1%，对于RINI为72.2%，研究任务权重相等。相较于同证据直接修订，改进幅度为33.0个百分点。修订后的提案保留了其研究问题和技术方法。这些结果促使在使用文献生成和修订研究提案时进行明确的贡献归属。
英文摘要
A research proposal can describe an established mechanism correctly while claiming to introduce it. We study whether providing the earlier paper corrects such contribution claims. Three controlled experiments compare proposals generated with a contribution-bearing prior and a same-topic control. Providing the prior yields no clear aggregate reduction in unsupported novelty. Human analysis of 175 interpretable exposed proposals finds that 137 recognize the prior's relevance, but 61 correctly attribute the established contribution. Of 71 proposed remaining distinctions, 37 are covered by the same prior. We introduce Research Idea Novelty Inspection (RINI), which audits contribution claims against evidence, checks the remaining distinction, and applies local revisions. Five human annotators evaluate 1,080 original-revision pairs across three methods. On the same 240 originals judged to require correction, successful repair is 11.7% for Self-Revision, 39.1% for Retrieve-and-Revise, and 72.2% for RINI, with research tasks weighted equally. The improvement over same-evidence direct revision is 33.0 percentage points. The revised proposals retain their research questions and technical methods. These results motivate explicit contribution attribution when using literature to generate and revise research proposals.
