38 citations · 118 across the 14 of their papers we have counts for
4 papers · 1 filter
True or False: Does the Deep Learning Model Learn to Detect Rumors?
Shiwen Ni, Jiawen Li, Hung-Yu Kao
It is difficult for humans to distinguish the true and false of rumors, but current deep learning models can surpass humans and achieve excellent accuracy on many rumor datasets. I…
HAT4RD: Hierarchical Adversarial Training for Rumor Detection on Social Media
Shiwen Ni, Jiawen Li, Hung-Yu Kao
With the development of social media, social communication has changed. While this facilitates people's communication and access to information, it also provides an ideal platform…
DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks
Shiwen Ni, Jiawen Li, Hung-Yu Kao
Adversarial training has been proven to be a powerful regularization method to improve the generalization of models. However, current adversarial training methods only attack the o…
Meet The Truth: Leverage Objective Facts and Subjective Views for Interpretable Rumor Detection
Jiawen Li, Shiwen Ni, Hung-Yu Kao
Existing rumor detection strategies typically provide detection labels while ignoring their explanation. Nonetheless, providing pieces of evidence to explain why a suspicious tweet…