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Forget generic legal LLMs – LegalMidm shows that focusing on specific Korean legal use cases, with data curated by legal pros, unlocks real-world performance gains.
LLMs can now perform inference without ever seeing raw text, opening the door to privacy-preserving applications without sacrificing performance.
Multilingual retrievers often prioritize irrelevant English documents over relevant foreign-language documents, even when the query is in that foreign language.
Forget just mining hard negatives: the secret to better knowledge distillation for retrieval lies in matching the *entire* score distribution of your teacher model.
