BEIR (Benchmarking-IR) is a heterogeneous, zero-shot information retrieval benchmark that consolidates 18 publicly available datasets from diverse retrieval tasks and domains (e.g., fact-checking, question-answering, biomedical IR, news retrieval, argument retrieval, duplicate question retrieval, citation prediction, tweets). It provides a common evaluation framework for IR models (lexical, sparse, dense, late-interaction, re-ranking) and is commonly reported using metrics such as nDCG@10 (average across datasets), MRR and recall. The BEIR code and data are available from the project GitHub and the Hugging Face dataset hub.
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