Towards Fine-Grained Reasoning for Fake News Detection

Jan 1, 2022ยท
Yiqiao Jin
Yiqiao Jin
,
Xiting Wang
,
Ruichao Yang
,
Yizhou Sun
,
Wei Wang
,
Hao Liao
,
Xing Xie
ยท 1 min read
Figure showing the main model architecture and workflow Our FinerFact model.
Abstract
We propose a fine-grained reasoning framework for fake news detection by following the human information-processing model and designing a prior-aware bi-channel kernel graph network.
Type
Publication
AAAI Conference on Artificial Intelligence 2022

Abstract

We propose a fine-grained reasoning framework for fake news detection by following the human information-processing model and designing a prior-aware bi-channel kernel graph network.

Keywords

Fake News Detection, Graph Neural Networks, Reasoning, Misinformation

Yiqiao Jin
Authors
CS PhD Student
My research interests include large language models (LLMs), multi-agent systems (MASs), and multimodal models.