Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Hu, Beizhe"'
Publikováno v:
CIKM 2024
Fake news detection plays a crucial role in protecting social media users and maintaining a healthy news ecosystem. Among existing works, comment-based fake news detection methods are empirically shown as promising because comments could reflect user
Externí odkaz:
http://arxiv.org/abs/2405.16631
Publikováno v:
IJCAI 2024
With the rapidly increasing application of large language models (LLMs), their abuse has caused many undesirable societal problems such as fake news, academic dishonesty, and information pollution. This makes AI-generated text (AIGT) detection of gre
Externí odkaz:
http://arxiv.org/abs/2402.09199
Autor:
Wang, Zhengjia, Wang, Danding, Sheng, Qiang, Cao, Juan, Su, Silong, Sun, Yifan, Hu, Beizhe, Ma, Siyuan
As the disruptive changes in the media economy and the proliferation of alternative news media outlets, news intent has progressively deviated from ethical standards that serve the public interest. News intent refers to the purpose or intention behin
Externí odkaz:
http://arxiv.org/abs/2312.16490
Publikováno v:
AAAI 2024
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 small language models (SLMs) due to their knowledge and capability limitat
Externí odkaz:
http://arxiv.org/abs/2309.12247
Autor:
Hu, Beizhe, Sheng, Qiang, Cao, Juan, Zhu, Yongchun, Wang, Danding, Wang, Zhengjia, Jin, Zhiwei
Fake news detection has been a critical task for maintaining the health of the online news ecosystem. However, very few existing works consider the temporal shift issue caused by the rapidly-evolving nature of news data in practice, resulting in sign
Externí odkaz:
http://arxiv.org/abs/2306.14728