Same Scores, Different Decisions: Evaluating JEV and Language Models for Legal Document Understanding
Aggregate accuracy summarizes how often a model is correct, but not which judgments remain correct when requests change. We evaluate Jev and nine language models on ContractNLI, with repeated requests that preserve the contract and target while varying visible hypotheses, requested answers, and output order. A four-model follow-up adds an equal-call repetition control and coverage of the remaining test contracts. Corrections and regressions can cancel, leaving unchanged accuracy despite changed decisions; consistent answers can also preserve errors. Majority voting over recorded responses yields small, uncertain gains, with repeated wrong answers accounting for much of the observed error....
| Authors | Fan Zhang, Yankai Chen, Zhuohan Xie et al. |
|---|---|
| Primary category | cs.CL |
| Published | 23 September 2026 |
| Last updated at source | 10 October 2026 |
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