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arXiv · 2610.20857

Idea2Prior: Auditable Paper Retrieval and Ranking from Research Ideas

Shitian Yang·Ruijie Tao·Jian Huang
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Abstract

Finding a paper from an informal research idea requires more than matching topic words: relevant work may use different terminology, and its distinguishing mechanism may be absent from the abstract. We present IDEA2PRIOR, an auditable literature-search system built on PaperArena. It combines multi-source discovery, identity verification, facet-based abstract assessment, semantic citation expansion, and joint Expert ranking. A retrieval-only mode ranks up to five papers from a shortlist of at most 60, using complete available abstracts and locally selected PDF evidence from five fixed acquisition attempts, without generating a long-form report. In a historical comparison covering ten queries from each of EASY, MEDIUM, and HARD, aggregate reported Hit@5 is 53.3% for IDEA2PRIOR, 43.3% for ChatGPT web Deep Research, and 36.7% for Gemini web Deep Research under the documented accounting convention. The advantage is concentrated in EASY and MEDIUM; ChatGPT leads on HARD. Selected IDEA2PRIOR runs average 8 minutes 53 seconds, compared with user-reported web averages of 5.2 and 4.7 minutes. A separate nine-query API sample averages $0.0945 per task; this is a historical cost observation, not a matched comparison with web subscription costs. Pairwise Top 5 coverage ranges from 6% to 34%, showing differing returned evidence sets. The system also exposes optional implementation analysis and citation-evolution tools. These results support targeted idea-to-paper retrieval while leaving general web research, forum search, and broader relevance evaluation open.

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Shitian Yang, Ruijie Tao, Jian Huang. 2026-10-16. Idea2Prior: Auditable Paper Retrieval and Ranking from Research Ideas. https://arxiv.org/abs/2610.20857

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