From Statute to Control Flow: Span-Grounded Deontic Trees for Defeasible Scope Parsing
Rule-following agents tasked with executing policies and regulations often fail via Silent Scope Omission (SSO): a model applies a general rule but silently drops nested exceptions or counter-exceptions, producing outputs that appear compliant yet break on important edge cases. Although such failures are often framed as an agentic-systems problem, the underlying bottleneck is statutory and policy understanding, a capability typically studied in legal NLP. However, most existing legal NLP benchmarks emphasize end-task outcomes, which can overlook the structural omissions that cause SSO. To diagnose and mitigate SSO, we introduce NormBench, a benchmark of 2,290 provisions spanning Chinese (...
| Authors | Jian Chen, Siyuan Li, Chucheng Wan et al. |
|---|---|
| Primary category | cs.CL |
| Published | 8 June 2026 |
| Last updated at source | 8 June 2026 |
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