Beyond Accuracy: Policy Invariance as a Reliability Test for LLM Safety Judges
LLM-as-a-Judge pipelines have become the de facto evaluator for agent safety, yet existing benchmarks treat their verdicts as ground-truth proxies without checking whether the verdicts depend on the agent's behavior or merely on how the evaluation policy happens to be worded. We argue that any trustworthy safety judge must satisfy a basic property we call policy invariance, and we operationalize it as three testable principles: rubric-semantics invariance under certified-equivalent rewrites, rubric-threshold invariance under intentional strict-to-lenient shifts, and ambiguity-aware calibration so that verdict instability concentrates on genuinely ambiguous cases. Instantiating these princ...
| Authors | Shihao Weng, Yang Feng, Xiaofei Xie |
|---|---|
| Primary category | cs.AI |
| Published | 7 May 2026 |
| Last updated at source | 7 May 2026 |
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