SynthGuard: An Open Platform for Detecting AI-Generated Multimedia with Multimodal LLMs
November 16, 2025 Β· Declared Dead Β· π arXiv.org
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Authors
Shail Desai, Aditya Pawar, Li Lin, Xin Wang, Shu Hu
arXiv ID
2511.12404
Category
cs.MM: Multimedia
Cross-listed
cs.AI,
cs.SD
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Artificial Intelligence (AI) has made it possible for anyone to create images, audio, and video with unprecedented ease, enriching education, communication, and creative expression. At the same time, the rapid rise of AI-generated media has introduced serious risks, including misinformation, identity misuse, and the erosion of public trust as synthetic content becomes increasingly indistinguishable from real media. Although deepfake detection has advanced, many existing tools remain closed-source, limited in modality, or lacking transparency and educational value, making it difficult for users to understand how detection decisions are made. To address these gaps, we introduce SynthGuard, an open, user-friendly platform for detecting and analyzing AI-generated multimedia using both traditional detectors and multimodal large language models (MLLMs). SynthGuard provides explainable inference, unified image and audio support, and an interactive interface designed to make forensic analysis accessible to researchers, educators, and the public. The SynthGuard platform is available at: https://in-engr-nova.it.purdue.edu/
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