ThinkDeception introduces MLLMs, a multimodal CoT dataset, and VAC-GRPO progressive RL to convert deception detection into interpretable reasoning and claims new SOTA accuracy plus rationale quality.
InProceedings of the 2015 ACM on International Conference on Multimodal Interaction(Seattle, Washington, USA)(ICMI ’15)
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ThinkDeception: A Progressive Reinforcement Learning Framework for Interpretable Multimodal Deception Detection
ThinkDeception introduces MLLMs, a multimodal CoT dataset, and VAC-GRPO progressive RL to convert deception detection into interpretable reasoning and claims new SOTA accuracy plus rationale quality.