mlsanityData to 7 Oct 2026

By Their Fruits You Will Know Them: Comparing Formalizations of Law by the Decisions They Encode

arXiv 2605.25186 ↗First posted 24 May 2026cs.CL cs.AIcited by 0

On the map: LLM reasoning → Reasoning for agents, planning and code

Abstract (arXiv)

Formalizing legal provisions promises machine-accessible law and automated legal reasoning, and recent LLMs make it tempting to generate such formalizations directly from statutory text. However, any formalization makes implicit interpretive choices whose consequences are hard to anticipate, especially if an LLM is the author. We present a method for systematically comparing different formalizations of the same legal provision by their inferences on individual cases. Given multiple formalizations of a provision, we match them at the node level, derive a shared interface for each pair from the matching, and use a SAT solver to enumerate the edge cases on which any two formalizations disagree. Selected edge cases are then verbalized into concrete factual scenarios that a legal expert can examine and act on. We apply our method to formalizations of ten EU provisions generated by nine frontier LLMs. We find that behavioral divergence between formalizations is essentially uncorrelated with their structural agreement and that the verbalized cases reveal qualitatively distinct types of disagreement, including divergences that mirror genuine controversies in the legal commentary.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 9 of its 35 references that are in the map. First posted on arXiv 24 May 2026.

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9 of 35 references.

References · 9

  1. 2024Autoformalize Mathematical Statements by Symbolic Equivalence and Semantic Consistencycited by 39
  2. 2024Schema Matching with Large Language Models: an Experimental Studycited by 19
  3. 2021Catala: A Programming Language for the Lawcited by 18
  4. 2023From Text to Structure: Using Large Language Models to Support the Development of Legal Expert Systemscited by 17
  5. 2021The Legislative Recipe: Syntax for Machine-Readable Legislationcited by 2
  6. 2021Pacta sunt servanda: legal contracts in Stipulacited by 1
  7. 2022A systematic literature review on counterexample explanationcited by 1
  8. 2025Automated Consistency Analysis for Legal Contractscited by 1
  9. 2026From Legal Text to Executable Decision Models: Evaluating Structured Representations for Legal Decision Model Generationcited by 1

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  1. 2026Know Your Limits : On the Faithfulness of LLMs as Solvers and Autoformalizers in Legal Reasoning
  2. 2024Argumentative Large Language Models for Explainable and Contestable Claim Verification
  3. 2023LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
  4. 2026Can LLMs Reason in a Legally Meaningful Manner? A Small-scale Study on European Court of Human Rights Cases
  5. 2024Reframing Tax Law Entailment as Analogical Reasoning
  6. 2025Thinking Longer, Not Always Smarter: Evaluating LLM Capabilities in Hierarchical Legal Reasoning
  7. 2022The Legal Argument Reasoning Task in Civil Procedure
  8. 2026When Do LLMs Apply the Wrong Law? Diagnosing LLM Failures in Temporal Legal Reasoning