207 citations · 514 across the 25 of their papers we have counts for
10 papers · 1 filter
Exploring news intent and its application: A theory-driven approach
Zhengjia Wang, Danding Wang, Qiang Sheng +3
Understanding the intent behind information is crucial. However, news as a medium of public discourse still lacks a structured investigation of perceived news intent and its applic…
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…
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…
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…
Exploiting User Comments for Early Detection of Fake News Prior to Users' Commenting
Qiong Nan, Qiang Sheng, Juan Cao +4
Both accuracy and timeliness are key factors in detecting fake news on social media. However, most existing methods encounter an accuracy-timeliness dilemma: Content-only methods g…
Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detection
Beizhe Hu, Qiang Sheng, Juan Cao +4
Detecting fake news requires both a delicate sense of diverse clues and a profound understanding of the real-world background, which remains challenging for detectors based on smal…