研究
推动AI 信任科学的发展
我们的研究聚焦于深度伪造检测、合成媒体取证以及对抗鲁棒性。我们公开发布研究成果，以推动该领域的发展，并帮助客户始终领先于新兴威胁。
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研究论文
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研究领域
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开放数据集
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即将推出
出版物与报告
来自 Scam AI 团队的研究，涵盖深度伪造检测、文档伪造、年龄估计等多个方向。
Document Forgery
- DOCFORGE-BENCH: A Comprehensive Benchmark for Document Forgery Detection and Analysis
Zengqi Zhao, Weidi Xia, Peter Wei, Yan Zhang, Yiyi Zhang, Jane Mo, Tiannan Zhang, Yuanqin Dai, Zexi Chen, Simiao Ren
在 arXiv 上查看 - When the Forger Is the Judge: GPT-Image-2 Cannot Recognize Its Own Faked Documents
Jiaqi Wu, Yuchen Zhou, Dennis Tsang Ng, Xingyu Shen, Kidus Zewde, Ankit Raj, Tommy Duong, Simiao Ren
在 arXiv 上查看 - AIForge-Doc: A Benchmark for Detecting AI-Forged Tampering in Financial and Form Documents
Jiaqi Wu, Yuchen Zhou, Muduo Xu, Zisheng Liang, Simiao Ren, Jiayu Xue, Meige Yang, Siying Chen, Jingheng Huan
在 arXiv 上查看 - Can Multi-modal (reasoning) LLMs detect document manipulation?
Zisheng Liang, Kidus Zewde, Rudra Pratap Singh, Disha Patil, Zexi Chen, Jiayu Xue, Yao Yao, Yifei Chen, Qinzhe Liu, Simiao Ren
在 Scholar 上查看
Age Estimation
- Can a Teenager Fool an AI? Evaluating Low-Cost Cosmetic Attacks on Age Estimation Systems
Xingyu Shen, Tommy Duong, Xiaodong An, Zengqi Zhao, Zebang Hu, Haoyu Hu, Ziyou Wang, Finn Guo, Simiao Ren
在 arXiv 上查看 - Out of the box age estimation through facial imagery: A Comprehensive Benchmark of Vision-Language Models vs. out-of-the-box Traditional Architectures
Simiao Ren, Xingyu Shen, Ankit Raj, Albert Dai, Caroline Zhang, Yuan Xu, Zexi Chen, Siqi Wu, Chen Gong, Yuxin Zhang
在 arXiv 上查看
AI-Generated Detection
- GPT-Image-2 in the Wild: A Twitter Dataset of Self-Reported AI-Generated Images from the First Week of Deployment
Kidus Zewde, Simiao Ren, Xingyu Shen, Jenny Wu, Yuchen Zhou, Tommy Duong, Zikang Zhang, Ethan Traister
在 arXiv 上查看 - How well are open sourced AI-generated image detection models out-of-the-box: A comprehensive benchmark study
Simiao Ren, Yuchen Zhou, Xingyu Shen, Kidus Zewde, Tommy Duong, George Huang, Neo Tiangratanakul, Dennis Ng, En Wei, Jiayu Xue
在 arXiv 上查看
Deepfake Detection
- Do deepfake detectors work in reality?
Simiao Ren, Disha Patil, Kidus Zewde, Dennis Ng, Hengwei Xu, Shengkai Jiang, Ramini Desai, Ning-Yau Cheng, Yining Zhou, Ragavi Muthukrishnan
在 Scholar 上查看 - Can Multi-modal (reasoning) LLMs work as deepfake detectors?
Simiao Ren, Yao Yao, Kidus Zewde, Zisheng Liang, Ning-Yau Cheng, Xiaoou Zhan, Qinzhe Liu, Yifei Chen, Hengwei Xu
在 Scholar 上查看
Interview Tech
数据集
精选数据集，帮助研究人员对检测模型进行基准测试。每个数据集都有独立页面，包含引用信息、论文链接以及需邮箱验证的下载入口。
A real-world faceswap collection used to evaluate deepfake detectors against in-the-wild manipulations rather than lab-only synthetics.
Financial and form documents tampered by a suite of AI editing tools, paired with originals — used to benchmark document forgery detectors.
A v2 expansion of AIForge-Doc covering GPT-Image-2 generated tampering — used in the 'When the Forger Is the Judge' benchmark.
Self-reported AI-generated images collected from Twitter during the first week of GPT-Image-2 deployment — captures real-world distribution shift.
Faces with low-cost cosmetic adversarial perturbations designed to defeat age estimation systems — used in 'Can a Teenager Fool an AI?'.
Fully synthetic receipts generated by GPT-4o, paired with a human-study evaluation of detectability — used for AI-generated document forensics research.
Synthetic eye-movement trajectories rendered through a 3D eye simulator, replaying real reading paths — used for script reading detection research.