ClaimRAG-LAW is a French-English legal RAG benchmark with claim-level granularity for experts and non-experts that reveals limitations in current retrieval and generation performance.
InProceedings of the 38th AAAI Conference on Arti- ficial Intelligence, pages 18642–18650
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LegalSearch-R1 trains a 7B agent via RL on multi-period legal data with hybrid RAG/web search to improve temporal consistency, reporting 12.9-29.8% gains over SOTA and 57.7-80.3% on consistency metrics across 13 tasks.
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Fine-grained Claim-level RAG Benchmark for Law
ClaimRAG-LAW is a French-English legal RAG benchmark with claim-level granularity for experts and non-experts that reveals limitations in current retrieval and generation performance.
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Can LLMs Time Travel? Enhancing Temporal Consistency in Legal Agentic Search through Reinforcement Learning
LegalSearch-R1 trains a 7B agent via RL on multi-period legal data with hybrid RAG/web search to improve temporal consistency, reporting 12.9-29.8% gains over SOTA and 57.7-80.3% on consistency metrics across 13 tasks.