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arXiv · 2603.22973

Where Experts Disagree, Models Fail: Detecting Implicit Legal Citations in French Court Decisions

Avrile Floro·Tamara Dhorasoo·Soline Pellez·Nils Holzenberger
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Abstract

Applying computational methods to law at scale requires separating genuine legal reasoning from surface similarity. We study this through a concrete task: detecting implicit citations of the French Civil Code, where a court applies a statutory rule without naming it: a post-hoc question about the reasoning a court actually used. We release a benchmark of 1,015 passage-article pairs annotated by three legal experts. Our central finding is that their disagreement is itself informative: the third of cases the experts dispute are where models fail. Our best ensemble reaches an F1 score of 0.70 overall. Yet, two-thirds of its false positives fall on those disputed cases, a concentration that holds across all ten models we evaluate. Disagreement is a signal of intrinsic difficulty, not annotation noise. This should not block useful tools, however: reframed as top-$k$ ranking with multi-model consensus, the same signals reach 76% precision for the top-200 candidates without supervision.

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Avrile Floro, Tamara Dhorasoo, Soline Pellez, Nils Holzenberger. 2026-03-24. Where Experts Disagree, Models Fail: Detecting Implicit Legal Citations in French Court Decisions. https://arxiv.org/abs/2603.22973

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