5 citations · 5 across the 5 of their papers we have counts for
7 papers
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…
BusterX: MLLM-Powered AI-Generated Video Forgery Detection and Explanation
Haiquan Wen, Yiwei He, Zhenglin Huang +7
As generative video models become increasingly realistic, detecting AI-generated videos requires systems that offer both accuracy and interpretability. However, applying Multimodal…
Safe Multi-Agent Behavior Must Be Maintained, Not Merely Asserted: Constraint Drift in LLM-Based Multi-Agent Systems
Tianxiao Li, Yixing Ma, Haiquan Wen +4
Modern LLM based agents are no longer passive text generators. They read repositories, call tools, browse the web, execute code, maintain memory, communicate with other agents, and…
Omni-Fake: Benchmarking Unified Multimodal Social Media Deepfake Detection
Tianxiao Li, Zhenglin Huang, Haiquan Wen +10
Multimodal deepfakes are proliferating on social media and threaten authenticity, information integrity, and digital forensics. Existing benchmarks are constrained by their single-…
Think and Answer ME: Benchmarking and Exploring Multi-Entity Reasoning Grounding in Remote Sensing
Shuchang Lyu, Haiquan Wen, Guangliang Cheng +5
Recent advances in reasoning language models and reinforcement learning with verifiable rewards have significantly enhanced multi-step reasoning capabilities. This progress motivat…
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…