AI RESEARCH
ReAlign: Generalizable Image Forgery Detection via Reasoning-Aligned Representation
arXiv CS.CV
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ArXi:2605.16080v1 Announce Type: new The rise of AI-generated images (AIGIs) poses growing challenges for digital authenticity, prompting the need for efficient, generalizable image forgery detection systems. Existing methods, whether non-LLM-based or LLM-based, exhibit distinct advantages and limitations. While non-LLM-based models offer efficient low-level artifact detection, they often lack semantic understanding. Conversely, LLM-based methods provide strong semantic reasoning and explainability but are computationally intensive and less sensitive to subtle visual artifacts.