7 papers
ThinkOmni: A Reasoning-Driven Omni-Modal LLM Framework for Audio Forgery Detection and Localization
Yuxiong Xu, Kaiqing Lin, Bin Li +2
Existing audio forgery detection and localization (AFDL) methods often overfit dataset-specific low-level artifacts, limiting their generalization to subtle, localized, and unseen…
AgentFoX: LLM Agent-Guided Fusion with eXplainability for AI-Generated Image Detection
Yangxin Yu, Yue Zhou, Bin Li +4
The realism of AI-generated images (AIGI) poses increasing challenges for reliable forensic detection, where heterogeneous expert detectors may produce conflicting predictions acro…
ForensicsTok: Forensics-Guided Tokenized Modeling for Image Tampering Localization
Lei Xu, Haowei Wang, Shen Chen +3
Multi-modal Large Language Models (MLLMs) offer powerful reasoning for forensic tasks, yet existing approaches utilizing exogenous segmentation decoders often suffer from suboptima…
Deep Residual Injection for Full-Spectrum Forensic Signal Perception in Multimodal Large Language Models
Kaiqing Lin, Zhiyuan Yan, Ruoxin Chen +8
Multimodal large language models (MLLMs) have been increasingly adopted in forensics for their robust semantic understanding. As AI-generated images become realistic, semantic-leve…
Guard Me If You Know Me: Protecting Specific Face-Identity from Deepfakes
Kaiqing Lin, Zhiyuan Yan, Ke-Yue Zhang +7
Securing personal identity against deepfake attacks is increasingly critical in the digital age, especially for celebrities and political figures whose faces are easily accessible…
Seeing Before Reasoning: A Unified Framework for Generalizable and Explainable Fake Image Detection
Kaiqing Lin, Zhiyuan Yan, Ruoxin Chen +7
Detecting AI-generated images with multimodal large language models (MLLMs) has gained increasing attention, due to their rich world knowledge, common-sense reasoning, and potentia…