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abdurrahmanbutlerย 
posted an update 10 days ago
Post
2516
๐ŸŽ‰ I am excited to share news of a project my brother, Umar Butler, and I have been working on for what feels like an eternity now.

๐ˆ๐ง๐ญ๐ซ๐จ๐๐ฎ๐œ๐ข๐ง๐  ๐Œ๐‹๐„๐ โ€” ๐ญ๐ก๐ž ๐Œ๐š๐ฌ๐ฌ๐ข๐ฏ๐ž ๐‹๐ž๐ ๐š๐ฅ ๐„๐ฆ๐›๐ž๐๐๐ข๐ง๐  ๐๐ž๐ง๐œ๐ก๐ฆ๐š๐ซ๐ค.

A suite of 10 high-quality English legal IR datasets, designed by legal experts to set a new standard for comparing embedding models.

Whether youโ€™re exploring legal RAG on your home computer, or running enterprise-scale retrieval, apples-to-apples evaluation is crucial. Thatโ€™s why weโ€™ve open-sourced everything - including our 7 brand-new, hand-crafted retrieval datasets. All of these datasets are now live on Hugging Face.

Any guesses which embedding model leads on legal retrieval?

๐‡๐ข๐ง๐ญ: itโ€™s not OpenAI or Google - they place 7th and 9th on our leaderboard.

To do well on MLEB, embedding models must demonstrate both extensive legal domain knowledge and strong legal reasoning skills.

https://huggingface.co/blog/isaacus/introducing-mleb

@abdurrahmanbutler I'm proud to have worked with you on this! MLEB is truly monumental. Given how often embeddings are used for law (and, consequently, how much money is on the line), it is crazy that we didn't have a truly fit-for-purpose benchmark for legal embeddings until today.