mlsanityData to 7 Oct 2026

The Massive Legal Embedding Benchmark (MLEB)

arXiv 2510.19365 ↗First posted 22 Oct 2025cs.CL cs.AI cs.IRcited by 6

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Abstract (arXiv)

We present the Massive Legal Embedding Benchmark (MLEB), the largest, most diverse, and most comprehensive open-source benchmark for legal information retrieval to date. MLEB consists of ten expert-annotated datasets spanning multiple jurisdictions (the US, UK, EU, Australia, Ireland, and Singapore), document types (cases, legislation, regulatory guidance, contracts, and literature), and task types (search, zero-shot classification, and question answering). Seven of the datasets in MLEB were newly constructed in order to fill domain and jurisdictional gaps in the open-source legal information retrieval landscape. We document our methodology in building MLEB and creating the new constituent datasets, and release our code, results, and data openly to assist with reproducible evaluations.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 7 of its 19 references that are in the map. First posted on arXiv 22 Oct 2025.

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7 of 19 references.

References · 7

  1. 2023LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Modelscited by 328
  2. 2021CUAD: An Expert-Annotated NLP Dataset for Legal Contract Reviewcited by 232
  3. 2021ContractNLI: A Dataset for Document-level Natural Language Inference for Contractscited by 145
  4. 2024LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domaincited by 113
  5. 2025A Reasoning-Focused Legal Retrieval Benchmarkcited by 37
  6. 2019Plain English Summarization of Contractscited by 28
  7. 2021Inscriptis -- A Python-based HTML to text conversion library optimized for knowledge extraction from the Webcited by 6

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