no code implementations • 6 May 2024 • Bo wang, Jing Ma, Hongzhan Lin, Zhiwei Yang, Ruichao Yang, Yuan Tian, Yi Chang
To detect fake news from a sea of diverse, crowded and even competing narratives, in this paper, we propose a novel defense-based explainable fake news detection framework.
1 code implementation • 24 Jan 2024 • Hongzhan Lin, Ziyang Luo, Wei Gao, Jing Ma, Bo wang, Ruichao Yang
Then we propose to fine-tune a small language model as the debate judge for harmfulness inference, to facilitate multimodal fusion between the harmfulness rationales and the intrinsic multimodal information within memes.
no code implementations • 3 Jan 2024 • Hongzhan Lin, Ziyang Luo, Bo wang, Ruichao Yang, Jing Ma
The exponential growth of social media has profoundly transformed how information is created, disseminated, and absorbed, exceeding any precedent in the digital age.
1 code implementation • 25 Oct 2023 • Ruichao Yang, Wei Gao, Jing Ma, Hongzhan Lin, Zhiwei Yang
This model only requires bag-level labels for training but is capable of inferring both sentence-level misinformation and article-level veracity, aided by relevant social media conversations that are attentively contextualized with news sentences.
no code implementations • 4 Apr 2023 • Hongzhan Lin, Jing Ma, Ruichao Yang, Zhiwei Yang, Mingfei Cheng
The truth is significantly hampered by massive rumors that spread along with breaking news or popular topics.
no code implementations • 6 Apr 2022 • Ruichao Yang, Jing Ma, Hongzhan Lin, Wei Gao
The diffusion of rumors on microblogs generally follows a propagation tree structure, that provides valuable clues on how an original message is transmitted and responded by users over time.
1 code implementation • 13 Sep 2021 • Yiqiao Jin, Xiting Wang, Ruichao Yang, Yizhou Sun, Wei Wang, Hao Liao, Xing Xie
The detection of fake news often requires sophisticated reasoning skills, such as logically combining information by considering word-level subtle clues.