Preprint Open access
Agentic Tool-Augmented Reasoning for Explainable Image Forgery Detection
Conventional image forgery detection methods produce binary scores or pixel-level masks without interpretable evidence, while recent multimodal large language model (MLLM)-based approaches generate post-hoc explanations of predetermined classification results rather than reasoning from evidence. Inspired by the forensi …