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20232026
most citedFSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learning

10 citations · 15 across the 18 of their papers we have counts for

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6 papers · 1 filter

cs.SD2026

Task-Aware Joint Pruning and Distillation for Efficient Audio Deepfake Detection

Miao He, Peng Cheng, Zhongjie Ba +4

Advances in speech synthesis have made deepfake speeches increasingly convincing, posing growing threats to security. While self-supervised learning (SSL) based detectors achieve s…

cs.CV2026

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection

Haoyu Wang, Yiming Qin, Zhongjie Ba +4

AI-generated images have proliferated rapidly, motivating extensive research. Most existing AI-generated image detectors are developed and evaluated under image-free generation par…

cs.CR2026

"Training robust watermarking model may hurt authentication!'' Exploring and Mitigating the Identity Leakage in Robust Watermarking

Xinyu Zhang, Ziping Dong, Qingyu Liu +3

The rapid advancement of generative AI has underscored the critical need for identifying image ownership and protecting copyrights. This makes post-processing image watermarking an…

cs.AI2026★ 1 cited

When AI reviews science: Can we trust the referee?

Jialiang Wang, Yuchen Liu, Hang Xu +7

The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the same time, modern large langu…

cs.CV2026

When Detectors Forget Forensics: Blocking Semantic Shortcuts for Generalizable AI-Generated Image Detection

Chao Shuai, Shaojing Fan, Chenlin Zou +6

The growing realism of generative models has blurred the boundary between real and synthetic content, posing significant challenges to reliable AI-generated image detection. Althou…

cs.SD2026

HyperPotter: Spell the Charm of High-Order Interactions in Audio Deepfake Detection

Qing Wen, Haohao Li, Zhongjie Ba +4

Advances in AIGC technologies have enabled the synthesis of highly realistic audio deepfakes capable of deceiving human auditory perception. Although numerous audio deepfake detect…