Cited sources more accurately when AI checks claims with steps
A three-part approach marks where to cite, how to search with purpose, and how to verify that sources back a claim.
- Publication
- arXiv
- Stage
- Preprint
- What we read
- Summary of the paper
- Authors
- Yuyang Huang, Bobo Li, Jiajia Song, Yuzhe Ding, Chong Teng, Fei Li, Donghong Ji
- Universities and research institutions
- Not yet supplied in verified metadata; the Brief does not guess.
Institution metadata: OpenAlex record ↗
What they did and found
The method splits finding quotes, picking purposeful search terms, and confirming that each source backs the claim, so references reflect real arguments instead of word matches. The study shows higher exact-citation accuracy than some AI baselines in strict tests, with results changing by how scoring is done.
Why it matters
Better checks can reduce misattributions and boost reader trust, but they add steps before publishing and may take more time.
The method splits finding quotes, picking purposeful search terms, and confirming that each source backs the claim, so references reflect real arguments instead of word matches.
In practice, these steps can slow publishing but may cut misattributions and raise reader trust in references, a trade editors may weigh.
Original sources · 1
- ReCite: Agentic Reasoning for Faithful Citation ↗arXiv · 2026-09-08
Check the original paper for its authors, methods, version and access terms.
What remains uncertain
Exact-match scoring may miss close-but-relevant options; results cover computer-science style papers and controlled test sets.
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