FACADE: Uncovering Value Misalignment in LLM Judgments of Apparently Compliant Behavior

Behavior can follow an expected form while violating the value that form is meant to express. We call this form–value pattern Performative Compliance. We introduce FACADE, a benchmark for evaluating whether LLMs recognize this pattern in narratives, built on a Behavior–Value matrix with two independently manipulated dimensions: Behavior Adherence and Value Alignment. Combining them yields four types of depicted behavior: Full Compliance, Principled Compliance (deviation from behavioral form while preserving intent), Surface Compliance (form adherence without intent alignment), and Non-Compliance. Cultural norms serve as a natural testbed because each retained norm involves both an explicit behavioral expectation and an implicit social intent, making form–intent divergence concretely operationalizable. To improve contextual realism, we propose a news-augmented story generation pipeline grounded in real-world event patterns. Across 20 LLMs evaluated on 9,416 stories derived from source norms associated with 75 countries/regions, models reliably judge Full and Principled Compliance but perform substantially worse on Surface Compliance, often accepting outwardly compliant yet value-violating behavior as appropriate.