activity
20202024
most citedMUSER: A MUlti-Step Evidence Retrieval Enhancement Framework for Fake News Detection

41 citations · 65 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024★ 9 cited

Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors

Guanghua Li, Wensheng Lu, Wei Zhang +5

The proliferation of fake news has had far-reaching implications on politics, the economy, and society at large. While Fake news detection methods have been employed to mitigate th…

cs.SI2023★ 41 cited

MUSER: A MUlti-Step Evidence Retrieval Enhancement Framework for Fake News Detection

Hao Liao, Jiaohao Peng, Zhanyi Huang +4

The ease of spreading false information online enables individuals with malicious intent to manipulate public opinion and destabilize social stability. Recently, fake news detectio…

cs.LG2022

Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation

Zhihao Zhu, Chenwang Wu, Min Zhou +3

Recent studies show that Graph Neural Networks(GNNs) are vulnerable and easily fooled by small perturbations, which has raised considerable concerns for adapting GNNs in various sa…

cs.CL2021★ 13 cited

Towards Fine-Grained Reasoning for Fake News Detection

Yiqiao Jin, Xiting Wang, Ruichao Yang +4

The detection of fake news often requires sophisticated reasoning skills, such as logically combining information by considering word-level subtle clues. In this paper, we move tow…

cs.SI2020★ 2 cited

Fake News Detection through Graph Comment Advanced Learning

Hao Liao, Qixin Liu, Kai Shu +1

Disinformation has long been regarded as a severe social problem, where fake news is one of the most representative issues. What is worse, today's highly developed social media mak…