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.