University of Illinois 论文提出 ClaimNov 逐项评估研究提案新颖性
University of Illinois 论文提出 ClaimNov，将研究提案拆分为多项主张并逐项匹配既有论文，以辅助判断新颖性。部署中的整体审查识别出全部 380 个伪装抄袭案例，却拒绝了后来发表的 96% 研究想法；ClaimNorm 识别出 97% 抄袭案例，仅拒绝其中 1.5%。论文建议逐项评分，并保留建立在 1 项已知结果之上的提案。
New University of Illinois paper finds that when AI decides if a research idea is new enough to work on, it often says no to ideas that human scientists later publish.
AI scientist pipelines run a novelty check to decide which generated ideas get compute. These checks judge a whole proposal at once, though most real papers build on some earlier contributions.
They built ClaimNov, which splits a proposal into a few claims, matches each against claims from prior papers, and gives a judge the claim-by-claim evidence.
A deployed check caught all 380 disguised copies but also rejected 96% of ideas researchers later published. ClaimNov caught 97% of copies while rejecting only 1.5% of those ideas.
If your pipeline filters ideas for novelty, score claims separately and keep proposals that build on 1 known result instead of discarding them.
来源：rohanpaul_ai · x.com