MAC-Bench is a new adversarial benchmark that converts legal texts into executable scenarios via the SERV pipeline to measure procedural compliance in multi-agent LLM systems using CSR and MG metrics.
Natural language processing for the legal domain: A survey of tasks, datasets, models, and challenges
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In 14 interviews, U.S. public defense professionals said AI is most helpful for evidence investigation and least helpful for courtroom advocacy and strategy.
A RAG pipeline using BM25 retrieval and GPT-o3 generation achieves 91% Precision@1 and 85% truthfulness for Nepali legal question answering on a curated 100-query benchmark.
citing papers explorer
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Beyond Goodhart's Law: A Dynamic Benchmark for Evaluating Compliance in Multi-Agent Systems
MAC-Bench is a new adversarial benchmark that converts legal texts into executable scenarios via the SERV pipeline to measure procedural compliance in multi-agent LLM systems using CSR and MG metrics.
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How Can AI Augment Access to Justice? Public Defenders' Perspectives on AI Adoption
In 14 interviews, U.S. public defense professionals said AI is most helpful for evidence investigation and least helpful for courtroom advocacy and strategy.
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Retrieval Augmented Generation Framework for the Nepali Legal Domain Question Answering
A RAG pipeline using BM25 retrieval and GPT-o3 generation achieves 91% Precision@1 and 85% truthfulness for Nepali legal question answering on a curated 100-query benchmark.