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New RATIO benchmark evaluates scientific literature retrieval for ideation

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced RATIO, a new benchmark designed to evaluate retrieval systems across different scientific literature ideation operations. This benchmark categorizes retrieval into three types: Address (finding approaches for problems), Broaden (retrieving more general concepts), and Specify (finding concrete instantiations). RATIO is built using millions of full-text papers and employs a novel discourse-marker distant supervision method, enhanced by LLM and human validation, to create a scalable framework for training and assessing retrieval components that support literature-grounded scientific inspiration. AI

IMPACT Establishes a new evaluation framework for retrieval systems supporting scientific ideation, potentially improving AI's ability to assist researchers.

RANK_REASON The item describes a new benchmark and methodology for scientific literature retrieval, published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New RATIO benchmark evaluates scientific literature retrieval for ideation

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The item describes a new benchmark and methodology for scientific literature retrieval, published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Tom Hope ·

    RATIO: A Benchmark for Retrieval Across Typed Ideation Operations in Scientific Literature

    Retrieved scientific literature can serve as inspiration for both human and AI scientists. Inspiration can take different forms: prior work may directly suggest how to address a problem, or surface directions at different levels of abstraction - zooming out to a more general view…

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