← 研踪 PaperTrailACL Anthology · ACL 2026:acl:2026.acl-long.2166 · 记录 #1
Monotonic Scaffolding as a Diagnostic Lens for Legal Reasoning in LLMs
来源日期（仅到月份） 2026-07
来源记录日期 2026-07
雷达观测 2026-11-01 21:46
摘要
Modern evaluation of Legal QA systems is shifting from terminal accuracy toward process-aware analyses of model reasoning. We propose a diagnostic framework grounded in monotonic pedagogical scaffolding, where language models receive gold-standard, case-relevant information across stages aligned with the canonical legal framework FIRAC — Facts, Issue, Rules, Application, Conclusion. By strictly adding solution-relevant content at each step, we introduce a controlled monotonic intervention that allows for the evaluation of reasoning trajectories rather than isolated outcomes.This longitudinal design enables the introduction of two transition-based diagnostics: Errors-to-Success (E2S) quantifies the guidance required to reach correctness, while Success-to-Errors (S2E) measures the fragility of that correctness under additional structure. These local patterns define a global robustness criterion termed Stable Accuracy, which credits a response only if the model maintains correctness throughout all scaffolding stages and enforces a higher bar for correctness by distinguishing sustained reasoning from transient patterns.We instantiate the framework on 3,123 Brazilian Bar Exam questions paired with expert-annotated explanations. Our findings reveal model instability patterns hidden from accuracy-only metrics and demonstrate that terminal accuracy systematically overestimates legal reasoning competence. To test the robustness of our diagnostics, we also evaluate a majority-vote aggregation across multiple reasoning samples, finding that the observed instability patterns persist under this stronger inference setting. Furthermore, principal component analysis indicates that legal domains cluster into distinct regions, suggesting systematic differences in reasoning demands across domains. While focused on the legal domain, our evaluation protocol is generalizable to any task with a staged reasoning structure.
论文发现出处
这些页面提供论文线索，不代表同行评审或质量认证。
观测到的版本
平台记录号代表本站观测到的元数据变化，不是作者修订号。来源日期仅到月份或年份时，按该月或该年首日存档。
记录 #1 · 2026-07 · 最新观测版本
Monotonic Scaffolding as a Diagnostic Lens for Legal Reasoning in LLMs
Modern evaluation of Legal QA systems is shifting from terminal accuracy toward process-aware analyses of model reasoning. We propose a diagnostic framework grounded in monotonic pedagogical scaffolding, where language models receive gold-standard, case-relevant information across stages aligned with the canonical legal framework FIRAC — Facts, Issue, Rules, Application, Conclusion. By strictly adding solution-relevant content at each step, we introduce a controlled monotonic intervention that allows for the evaluation of reasoning trajectories rather than isolated outcomes.This longitudinal design enables the introduction of two transition-based diagnostics: Errors-to-Success (E2S) quantifies the guidance required to reach correctness, while Success-to-Errors (S2E) measures the fragility of that correctness under additional structure. These local patterns define a global robustness criterion termed Stable Accuracy, which credits a response only if the model maintains correctness throughout all scaffolding stages and enforces a higher bar for correctness by distinguishing sustained reasoning from transient patterns.We instantiate the framework on 3,123 Brazilian Bar Exam questions paired with expert-annotated explanations. Our findings reveal model instability patterns hidden from accuracy-only metrics and demonstrate that terminal accuracy systematically overestimates legal reasoning competence. To test the robustness of our diagnostics, we also evaluate a majority-vote aggregation across multiple reasoning samples, finding that the observed instability patterns persist under this stronger inference setting. Furthermore, principal component analysis indicates that legal domains cluster into distinct regions, suggesting systematic differences in reasoning demands across domains. While focused on the legal domain, our evaluation protocol is generalizable to any task with a staged reasoning structure.
查看此版本解读 →查看此版本原文 ↗