6 citations · 9 across the 14 of their papers we have counts for
8 papers · 1 filter
Rethinking Cross-Generator Image Forgery Detection through DINOv3
Zhenglin Huang, Jason Li, Haiquan Wen +7
As generative models become increasingly diverse and powerful, cross-generator detection has emerged as a new challenge. Existing detection methods often memorize artifacts of spec…
Spatial-DISE: A Unified Benchmark for Evaluating Spatial Reasoning in Vision-Language Models
Xinmiao Huang, Qisong He, Zhenglin Huang +5
Spatial reasoning ability is crucial for Vision Language Models (VLMs) to support real-world applications in diverse domains including robotics, augmented reality, and autonomous n…
RAIDX: A Retrieval-Augmented Generation and GRPO Reinforcement Learning Framework for Explainable Deepfake Detection
Tianxiao Li, Zhenglin Huang, Haiquan Wen +4
The rapid advancement of AI-generation models has enabled the creation of hyperrealistic imagery, posing ethical risks through widespread misinformation. Current deepfake detection…
BusterX++: Towards Unified Cross-Modal AI-Generated Content Detection and Explanation with MLLM
Haiquan Wen, Tianxiao Li, Zhenglin Huang +2
The rapid advancement of generative AI has substantially improved image and video synthesis, amplifying the risk of multimodal visual misinformation. Recent MLLMs have shown promis…
Towards Explainable Bilingual Multimodal Misinformation Detection and Localization
Yiwei He, Zhenglin Huang, Haiquan Wen +5
The increasing realism of multimodal content has made misinformation more subtle and harder to detect, especially in news media where images are frequently paired with bilingual (e…
So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection
Zhenglin Huang, Xiangtai Li, Xi Yang +6
Recent advances in AI-powered generative models have enabled the creation of increasingly realistic synthetic images, posing significant risks to information integrity and public t…