Reproduce “Inspire: Benchmarking Scientific Literature Search for Open Research Problems” on OpenResearch

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About this paper

Jianrong Ding, Zhengyan Shi, Jianyuan Zhong, Kai Qiu, Qi Dai, Yifan Yang, Chong Luo, Qiang Xu

INSPIRE evaluates agents searching redacted computer-science problems by measuring which graded cited antecedents they expose, select, and rank. Across 476 targets, Claude Opus 5 reaches 0.284 nDCG@10; it recovers at least one antecedent on 72.3% but at least three on 32.1%. Exposure shows the largest observed loss, while hindsight-SFT raises Qwen3.6-35B-A3B’s score from 0.082 to 0.166.

Key insights

  • Literature search is a changing process: agents must form and update their own working notion of relevance rather than apply a criterion supplied in advance.
  • Exposure is the largest measured loss point across evaluated systems; strong selection or ranking cannot recover useful papers that never appear in the search results.
  • The benchmark’s graded references capture a target paper’s realized citation lineage, not every work that could scientifically help solve the problem.

Summary by alphaXiv.

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