MAP-Law dynamically controls retrieval depth in legal AI by computing element coverage, evidence coverage, and marginal gain on a joint node graph, reaching 0.86 element coverage with 58% fewer rounds than fixed baselines on 50 labor-law cases.
Natural language processing in the legal domain
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MAP-Law: Coverage-Driven Retrieval Control for Multi-Turn Legal Consultation
MAP-Law dynamically controls retrieval depth in legal AI by computing element coverage, evidence coverage, and marginal gain on a joint node graph, reaching 0.86 element coverage with 58% fewer rounds than fixed baselines on 50 labor-law cases.