MM-DeceptionBench
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Debate with Images: Detecting Deceptive Behaviors in Multimodal Large Language Models
arXiv:2512.00349v3 Announce Type: replace Abstract: Are frontier AI systems becoming more capable? Yet such progress is not an unalloyed blessing but rather a Trojan horse: behind their performance leaps lie more insidious and destructive safety risks, namely deception. Unlike hallucination, which arises from insufficient capability and leads to mistakes, deception represents a deeper threat in which models deliberately mislead users through complex reasoning and insincere responses.