Can Large Language Models Understand Content and Propagation for
Misinformation Detection: An Empirical Study

Can Large Language Models Understand Content and Propagation for Misinformation Detection: An Empirical Study

21 November 2023

Papers citing "Can Large Language Models Understand Content and Propagation for Misinformation Detection: An Empirical Study"

10 / 10 papers shown

Title
Capabilities of GPT-4 on Medical Challenge Problems Harsha Nori Nicholas King S. McKinney Dean Carignan Eric Horvitz LM&MA ELM AI4MH 107 796 0 20 Mar 2023
COLD: A Benchmark for Chinese Offensive Language Detection Deng Jiawen Jingyan Zhou Hao Sun Chujie Zheng Fei Mi Helen M. Meng Minlie Huang 60 108 0 16 Jan 2022
GLM: General Language Model Pretraining with Autoregressive Blank Infilling Zhengxiao Du Yujie Qian Xiao Liu Ming Ding J. Qiu Zhilin Yang Jie Tang BDL AI4CE 109 1,535 0 18 Mar 2021
AngryBERT: Joint Learning Target and Emotion for Hate Speech Detection Rabiul Awal Rui Cao Roy Ka-wei Lee Sandra Mitrović 41 42 0 14 Mar 2021
Early Detection of Fake News by Utilizing the Credibility of News, Publishers, and Users Based on Weakly Supervised Learning Chunyuan Yuan Qianwen Ma Wei Zhou Jizhong Han Songlin Hu GNN 193 69 0 08 Dec 2020
FANG: Leveraging Social Context for Fake News Detection Using Graph Representation Van-Hoang Nguyen Kazunari Sugiyama Preslav Nakov Min-Yen Kan GNN FedML 59 284 0 18 Aug 2020
DeBERTa: Decoding-enhanced BERT with Disentangled Attention Pengcheng He Xiaodong Liu Jianfeng Gao Weizhu Chen AAML 129 2,724 0 05 Jun 2020
GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media Yi-Ju Lu Cheng-Te Li GNN 94 393 0 24 Apr 2020
Do Sentence Interactions Matter? Leveraging Sentence Level Representations for Fake News Classification Vaibhav Vaibhav Raghuram Mandyam Annasamy Eduard H. Hovy GNN 84 66 0 27 Oct 2019
Different Absorption from the Same Sharing: Sifted Multi-task Learning for Fake News Detection Lianwei Wu Y. Rao Haolin Jin Ambreen Nazir Ling Sun FedML MoE 41 57 0 04 Sep 2019

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