开源工具SynthGuard用多模态大模型检测AI生成内容，支持图文并解释结果。
SynthGuard: An Open Platform for Detecting AI-Generated Multimedia with Multimodal LLMs
- 结合传统检测器与多模态大模型进行跨模态分析。
- 支持图像与音频的统一检测，提供可解释的推理过程。
- 界面友好，适合研究人员、教育者和公众使用。
人工智能使人们能以前所未有的便捷方式生成图像、音频和视频，丰富了教育、沟通与创意表达。然而，AI生成媒体的迅速发展也带来了严重风险，包括虚假信息、身份滥用以及公众信任的削弱，因为合成内容越来越难以与真实内容区分。尽管深度伪造检测技术已取得进展，但许多现有工具仍为闭源、模态有限或缺乏透明度与教育价值，用户难以理解检测决策依据。为弥补这些不足，我们提出SynthGuard——一个开放、易用的平台，利用传统检测器和多模态大语言模型（MLLMs）检测与分析AI生成的多媒体内容。SynthGuard提供可解释的推理、统一的图像与音频支持，以及交互式界面，使取证分析对研究者、教育工作者和公众都更易获取。该平台已上线：https://in-engr-nova.it.purdue.edu/
原文摘要 · Abstract (English)
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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