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Fine-tuning dense retrievers on a mix of domain-specific and general question-answering data achieves surprisingly robust performance across diverse legal search tasks, outperforming models trained solely on legal data.
Brazilian legal IR gets a much-needed standardized benchmark, JU'A, revealing surprising trade-offs between retrieval methods across different legal domains.
