Author

Andrew M. Bean

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Review Aug 2026

ContractScrub: A benchmark for final review of legal contracts

Legal work, with its heavy reliance on processing large amounts of text, is often considered one of the domains most exposed to the use of LLMs. Contract ``scrubbing,''the final review of transactional agreements for errors and inconsistencies, is a particularly suitable task for automation, because it is routine, pain...

Yejin Bang, Kirsty Fielding, Brandan Oliver et al. · 0 citations

Preprint Aug 2026

InsufficiencyBench: Evaluating LLM legal advice on underspecified user queries

Legal AI systems are increasingly used to answer legal questions, yet existing benchmarks assume queries arrive fully specified. In practice, users omit facts that materially determine the legal outcome. We introduce InsufficiencyBench, the first legal benchmark targeting query-side insufficiency: whether a model recog...

S. J. Vincent, D. Calloway, Fangyi Yu et al. · 0 citations

Preprint Jun 2026

How sensitive do we want AI to be? Socio-communicative competencies of large language models in healthcare

Current LLMs lack the consistent and reliable socio-communicative skills needed for safe and effective use as healthcare advisors, and showed strength in non-hostility, mixed results in sensitivity and non-intrusiveness and performed poorly in structuring.

Dorothee Amelung, Andrew M. Bean, Sabine C. Herpertz et al. · 0 citations