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20212026
most citedGeneralizing to the Future: Mitigating Entity Bias in Fake News Detection

85 citations · 110 across the 13 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Multi-Tool Image Editing Attribution in Facial Forgery

Sheng Liu, Qiang Sheng, Danding Wang +3

As generative AI tools become increasingly powerful and easy to use, people can easily edit portrait images with a prompt, necessitating the task of image editing attribution, whic…

cs.CV20241 cited

FakingRecipe: Detecting Fake News on Short Video Platforms from the Perspective of Creative Process

Yuyan Bu, Qiang Sheng, Juan Cao +3

As short-form video-sharing platforms become a significant channel for news consumption, fake news in short videos has emerged as a serious threat in the online information ecosyst…

cs.CV2023

Rethinking Image Editing Detection in the Era of Generative AI Revolution

Zhihao Sun, Haipeng Fang, Xinying Zhao +2

The accelerated advancement of generative AI significantly enhance the viability and effectiveness of generative regional editing methods. This evolution render the image manipulat…

cs.CV2023

Adversarial Robust Memory-Based Continual Learner

Xiaoyue Mi, Fan Tang, Zonghan Yang +4

Despite the remarkable advances that have been made in continual learning, the adversarial vulnerability of such methods has not been fully discussed. We delve into the adversarial…

cs.CV2023

Topology-preserving Adversarial Training for Alleviating Natural Accuracy Degradation

Xiaoyue Mi, Fan Tang, Yepeng Weng +5

Despite the effectiveness in improving the robustness of neural networks, adversarial training has suffered from the natural accuracy degradation problem, i.e., accuracy on natural…

cs.CV2023

Model Synthesis for Zero-Shot Model Attribution

Tianyun Yang, Juan Cao, Danding Wang +1

Nowadays, generative models are shaping various fields such as art, design, and human-computer interaction, yet accompanied by challenges related to copyright infringement and cont…