4 citations · 4 across the 7 of their papers we have counts for
9 papers
IVT-Guard: All-in-One Reasoning Model for AI-Generated Content Detection
Hongwei Niu, Yunpeng Luo, Hanjun Li +6
The rapid proliferation of highly realistic AI-Generated Content (AIGC) necessitates robust and interpretable detection mechanisms. However, existing detectors are predominantly co…
ForensicConcept: Transferable Forensic Concepts for AIGI Detection
Menyanshu Zhou, Ziyin Zhou, Ke Sun +4
AI-generated image detectors achieve high accuracy on in-distribution data but often fail on unseen generators. A key obstacle to understanding this failure is the black-box nature…
Q-DeepSight: Incentivizing Thinking with Images for Image Quality Assessment and Refinement
Xudong Li, Jiaxi Tan, Ziyin Zhou +6
Image Quality Assessment (IQA) models are increasingly deployed as perceptual critics to guide generative models and image restoration. This role demands not only accurate scores b…
Tug-of-War within A Decade: Conflict Resolution in Vulnerability Analysis via Teacher-Guided Retrieval-Augmented Generations
Ziyin Zhou, Jianyi Zhang, Xu ji +3
Large Language Models (LLMs) are essential for analyzing and addressing vulnerabilities in cybersecurity. However, among over 200,000 vulnerabilities were discovered in the past de…
Towards Rationale-Answer Alignment of LVLMs via Self-Rationale Calibration
Yuanchen Wu, Ke Yan, Shouhong Ding +2
Large Vision-Language Models (LVLMs) have manifested strong visual question answering capability. However, they still struggle with aligning the rationale and the generated answer,…
AIGI-Holmes: Towards Explainable and Generalizable AI-Generated Image Detection via Multimodal Large Language Models
Ziyin Zhou, Yunpeng Luo, Yuanchen Wu +7
The rapid development of AI-generated content (AIGC) technology has led to the misuse of highly realistic AI-generated images (AIGI) in spreading misinformation, posing a threat to…
Exploring the Collaborative Advantage of Low-level Information on Generalizable AI-Generated Image Detection
Ziyin Zhou, Ke Sun, Zhongxi Chen +5
Existing state-of-the-art AI-Generated image detection methods mostly consider extracting low-level information from RGB images to help improve the generalization of AI-Generated i…
StealthDiffusion: Towards Evading Diffusion Forensic Detection through Diffusion Model
Ziyin Zhou, Ke Sun, Zhongxi Chen +3
The rapid progress in generative models has given rise to the critical task of AI-Generated Content Stealth (AIGC-S), which aims to create AI-generated images that can evade both f…
DiffusionFace: Towards a Comprehensive Dataset for Diffusion-Based Face Forgery Analysis
Zhongxi Chen, Ke Sun, Ziyin Zhou +4
The rapid progress in deep learning has given rise to hyper-realistic facial forgery methods, leading to concerns related to misinformation and security risks. Existing face forger…