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데이터셋 탐색

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관련 논문 311편

Benchmarking IR

BEIR
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BEIR (Benchmarking IR) is a heterogeneous benchmark containing different information retrieval (IR) tasks. Through BEIR, it is possible to systematically study the zero-shot generalization capabilities of multiple neural retrieval approaches. The benchmark contains a total of 9 information retrieval tasks (Fact Checking, Citation Prediction, Duplicate Question Retrieval, Argument Retrieval, News Retrieval, Question Answering, Tweet Retrieval, Biomedical IR, Entity Retrieval) from 19 different datasets: * MS MARCO * TREC-COVID * NFCorpus * BioASQ * Natural Questions * HotpotQA * FiQA-2018 * Signal-1M * TREC-News * ArguAna * Touche 2020 * CQADupStack * Quora Question Pairs * DBPedia * SciDocs * FEVER * Climate-FEVER * SciFact * Robust04