1 citations · 1 across the 7 of their papers we have counts for
7 papers
Harmful Visual Content Manipulation Matters in Misinformation Detection Under Multimedia Scenarios
Bing Wang, Ximing Li, Changchun Li +4
Nowadays, the widespread dissemination of misinformation across numerous social media platforms has led to severe negative effects on society. To address this challenge, the automa…
Enhancing Multimodal Misinformation Detection by Replaying the Whole Story from Image Modality Perspective
Bing Wang, Ximing Li, Yanjun Wang +4
Multimodal Misinformation Detection (MMD) refers to the task of detecting social media posts involving misinformation, where the post often contains text and image modalities. Howe…
Robust Misinformation Detection by Visiting Potential Commonsense Conflict
Bing Wang, Ximing Li, Changchun Li +4
The development of Internet technology has led to an increased prevalence of misinformation, causing severe negative effects across diverse domains. To mitigate this challenge, Mis…
Collaboration and Controversy Among Experts: Rumor Early Detection by Tuning a Comment Generator
Bing Wang, Bingrui Zhao, Ximing Li +3
Over the past decade, social media platforms have been key in spreading rumors, leading to significant negative impacts. To counter this, the community has developed various Rumor…
Why Misinformation is Created? Detecting them by Integrating Intent Features
Bing Wang, Ximing Li, Changchun Li +3
Various social media platforms, e.g., Twitter and Reddit, allow people to disseminate a plethora of information more efficiently and conveniently. However, they are inevitably full…
Harmfully Manipulated Images Matter in Multimodal Misinformation Detection
Bing Wang, Shengsheng Wang, Changchun Li +2
Nowadays, misinformation is widely spreading over various social media platforms and causes extremely negative impacts on society. To combat this issue, automatically identifying m…
Unsupervised Sentence Representation Learning with Frequency-induced Adversarial Tuning and Incomplete Sentence Filtering
Bing Wang, Ximing Li, Zhiyao Yang +3
Pre-trained Language Model (PLM) is nowadays the mainstay of Unsupervised Sentence Representation Learning (USRL). However, PLMs are sensitive to the frequency information of words…