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20232026
most citedTowards Explainable Fake Image Detection with Multi-Modal Large Language Models

2 citations · 4 across the 30 of their papers we have counts for

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13 papers · 1 filter

cs.CV2025

Locate-Then-Examine: Grounded Region Reasoning Improves Detection of AI-Generated Images

Yikun Ji, Yan Hong, Bowen Deng +5

The rapid growth of AI-generated imagery has blurred the boundary between real and synthetic content, raising practical concerns for digital integrity. Vision-language models (VLMs…

cs.CV2025

GAMMA: Generalizable Alignment via Multi-task and Manipulation-Augmented Training for AI-Generated Image Detection

Haozhen Yan, Yan Hong, Suning Lang +6

With generative models becoming increasingly sophisticated and diverse, detecting AI-generated images has become increasingly challenging. While existing AI-genereted Image detecto…

cs.SD2025

Generalizable Audio Deepfake Detection via Hierarchical Structure Learning and Feature Whitening in Poincaré sphere

Mingru Yang, Yanmei Gu, Qianhua He +7

Audio deepfake detection (ADD) faces critical generalization challenges due to diverse real-world spoofing attacks and domain variations. However, existing methods primarily rely o…

cs.CV2025

Veritas: Generalizable Deepfake Detection via Pattern-Aware Reasoning

Hao Tan, Jun Lan, Zichang Tan +7

Deepfake detection remains a formidable challenge due to the complex and evolving nature of fake content in real-world scenarios. However, existing academic benchmarks suffer from…

cs.CV2025

EMIT: Enhancing MLLMs for Industrial Anomaly Detection via Difficulty-Aware GRPO

Wei Guan, Jun Lan, Jian Cao +3

Industrial anomaly detection (IAD) plays a crucial role in maintaining the safety and reliability of manufacturing systems. While multimodal large language models (MLLMs) show stro…

cs.CV2025

Interpretable and Reliable Detection of AI-Generated Images via Grounded Reasoning in MLLMs

Yikun Ji, Hong Yan, Jun Lan +5

The rapid advancement of image generation technologies intensifies the demand for interpretable and robust detection methods. Although existing approaches often attain high accurac…

cs.CV2025

DS-VTON: An Enhanced Dual-Scale Coarse-to-Fine Framework for Virtual Try-On

Xianbing Sun, Yan Hong, Jiahui Zhan +5

Despite recent progress, most existing virtual try-on methods still struggle to simultaneously address two core challenges: accurately aligning the garment image with the target hu…

cs.CV2025★ 1 cited

Robustness in AI-Generated Detection: Enhancing Resistance to Adversarial Attacks

Sun Haoxuan, Hong Yan, Zhan Jiahui +6

The rapid advancement of generative image technology has introduced significant security concerns, particularly in the domain of face generation detection. This paper investigates…

cs.CV2025

Benchmarking Unified Face Attack Detection via Hierarchical Prompt Tuning

Ajian Liu, Haocheng Yuan, Xiao Guo +13

PAD and FFD are proposed to protect face data from physical media-based Presentation Attacks and digital editing-based DeepFakes, respectively. However, isolated training of these…

cs.CL2025

Keep the General, Inject the Specific: Structured Dialogue Fine-Tuning for Knowledge Injection without Catastrophic Forgetting

Yijie Hong, Xiaofei Yin, Xinzhong Wang +7

Large Vision Language Models have demonstrated impressive versatile capabilities through extensive multimodal pre-training, but face significant limitations when incorporating spec…

cs.CV2025★ 2 cited

Towards Explainable Fake Image Detection with Multi-Modal Large Language Models

Yikun Ji, Yan Hong, Jiahui Zhan +6

Progress in image generation raises significant public security concerns. We argue that fake image detection should not operate as a "black box". Instead, an ideal approach must en…

cs.CV2025

InterAnimate: Taming Region-aware Diffusion Model for Realistic Human Interaction Animation

Yukang Lin, Yan Hong, Zunnan Xu +10

Recent video generation research has focused heavily on isolated actions, leaving interactive motions-such as hand-face interactions-largely unexamined. These interactions are esse…

cs.LG2025

InsightVision: A Comprehensive, Multi-Level Chinese-based Benchmark for Evaluating Implicit Visual Semantics in Large Vision Language Models

Xiaofei Yin, Yijie Hong, Ya Guo +4

In the evolving landscape of multimodal language models, understanding the nuanced meanings conveyed through visual cues - such as satire, insult, or critique - remains a significa…