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New ProSearch benchmark highlights challenges in scientific protocol retrieval

Researchers have introduced ProSearch, a new benchmark designed to evaluate multi-constraint protocol retrieval systems within experimental science. This benchmark addresses the limitations of existing systems by incorporating realistic queries, complex experimental fields with dependencies, and explicit constraints including numerical and negation requirements. Experiments on ProSearch with 19 retrieval systems revealed that even the best-performing models achieved an average nDCG@10 of 0.290, highlighting joint constraint binding as a significant bottleneck. AI

IMPACT This benchmark could drive the development of more sophisticated AI systems for scientific research, improving the efficiency and accuracy of experimental design and reproduction.

RANK_REASON The cluster describes a new benchmark and associated research paper published on arXiv.

Read on arXiv cs.IR (Information Retrieval) →

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New ProSearch benchmark highlights challenges in scientific protocol retrieval

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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Wenliang Liang, Zhiyuan Ning, Haolin Chen, Yuanchun Zhou, Wenjuan Cui, Yi Du ·

    ProSearch: Benchmarking Multi-Constraint Protocol Retrieval in Experimental Science

    arXiv:2610.41396v1 Announce Type: cross Abstract: In AI for Science scenarios, experimental design and method reproduction require retrieving protocols that satisfy multiple interdependent constraints, yet existing benchmarks lack systematic evaluation of this capability. To addr…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Yi Du ·

    ProSearch: Benchmarking Multi-Constraint Protocol Retrieval in Experimental Science

    In AI for Science scenarios, experimental design and method reproduction require retrieving protocols that satisfy multiple interdependent constraints, yet existing benchmarks lack systematic evaluation of this capability. To address this gap, we introduce ProSearch, a benchmark …