Grounded but Misleading: Evaluating Semantic Alignment in AI-Generated Security Explanations 事件

Grounded but Misleading: Evaluating Semantic Alignment in AI-Generated Security Explanations arXiv:2602.05056v2 Announce Type: replace-cross Abstract: Online scams increasingly leverage fluent and context-aware social engineering strategies, creating growing demand for AI systems that explain why a message may be risky. However, explanations that cite detector-derived evidence may still semantically weaken or redirect the intended risk interpretation. We introduce VEXA: Verifying Semantic Expla