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New RAG Benchmark Launched for Drug Discovery PPIs

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced RAGPPI, a new benchmark designed to evaluate Retrieval-Augmented Generation (RAG) systems for identifying the biological impacts of protein-protein interactions (PPIs) in drug discovery. The benchmark consists of 4,420 question-answer pairs, with a gold-standard subset of 500 pairs created through expert annotation and a silver-standard set generated using an ensemble auto-evaluation LLM. RAGPPI aims to advance RAG systems for drug discovery applications by providing a dedicated resource for this specific task. AI

RANK_REASON The cluster describes a new academic paper introducing a benchmark dataset for AI research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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

New RAG Benchmark Launched for Drug Discovery PPIs

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The cluster describes a new academic paper introducing a benchmark dataset for AI research. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 Deutsch(DE) · Youngseung Jeon, Ziwen Li, Thomas Li, JiaSyuan Chang, Morteza Ziyadi, Xiang 'Anthony' Chen ·

    RAGPPI: RAG Benchmark for Protein-Protein Interactions in Drug Discovery

    arXiv:2505.23823v2 Announce Type: replace Abstract: Retrieving the biological impacts of protein-protein interactions (PPIs) is essential for target identification (Target ID) in drug development. Given the vast number of proteins involved, this process remains time-consuming and…

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