LegalCiteBench reveals that current LLMs achieve under 7% accuracy on closed-book legal citation retrieval and completion tasks, with misleading answer rates above 94% for nearly all tested models.
Journal of empirical legal studies , volume=
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A neuro-symbolic system is proposed that uses formal logic to constrain LLM outputs so legal inferences stay faithful to source text.
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LegalCiteBench: Evaluating Citation Reliability in Legal Language Models
LegalCiteBench reveals that current LLMs achieve under 7% accuracy on closed-book legal citation retrieval and completion tasks, with misleading answer rates above 94% for nearly all tested models.
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Bridging Legal Interpretation and Formal Logic: Faithfulness, Assumption, and the Future of AI Legal Reasoning
A neuro-symbolic system is proposed that uses formal logic to constrain LLM outputs so legal inferences stay faithful to source text.