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Fake News Detection
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Fake News Detection is a natural language processing task that involves identifying and classifying news articles or other types of text as real or fake. The goal of fake news detection is to develop algorithms that can automatically identify and flag fake news articles, which can be used to combat misinformation and promote the dissemination of accurate information.
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KEN: Knowledge Augmentation and Emotion Guidance Network for Multimodal Fake News Detection
Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection
Synergizing LLMs with Global Label Propagation for Multimodal Fake News Detection
Interpretable Graph Learning Over Sets of Temporally-Sparse Data
Improving Bangla Linguistics: Advanced LSTM, Bi-LSTM, and Seq2Seq Models for Translating Sylheti to Modern Bangla
KGAlign: Joint Semantic-Structural Knowledge Encoding for Multimodal Fake News Detection
MPPFND: A Dataset and Analysis of Detecting Fake News with Multi-Platform Propagation
The Truth Becomes Clearer Through Debate! Multi-Agent Systems with Large Language Models Unmask Fake News
Multimodal Fake News Detection: MFND Dataset and Shallow-Deep Multitask Learning
A Python Tool for Reconstructing Full News Text from GDELT
Adaptation Method for Misinformation Identification
Exploring Modality Disruption in Multimodal Fake News Detection
Deconfounded Reasoning for Multimodal Fake News Detection via Causal Intervention
FMNV: A Dataset of Media-Published News Videos for Fake News Detection
Multi-view autoencoders for Fake News Detection
Is Less Really More? Fake News Detection with Limited Information
Synthetic News Generation for Fake News Classification
Collaborative Evolution: Multi-Round Learning Between Large and Small Language Models for Emergent Fake News Detection
Is LLMs Hallucination Usable? LLM-based Negative Reasoning for Fake News Detection
ClaimTrust: Propagation Trust Scoring for RAG Systems
Revealing Hidden Mechanisms of Cross-Country Content Moderation with Natural Language Processing
Unseen Fake News Detection Through Casual Debiasing
External Reliable Information-enhanced Multimodal Contrastive Learning for Fake News Detection
Vision-Language Models Struggle to Align Entities across Modalities
An exploration of features to improve the generalisability of fake news detection models
Bangla Fake News Detection Based On Multichannel Combined CNN-LSTM
Advanced Text Analytics -- Graph Neural Network for Fake News Detection in Social Media
A Macro- and Micro-Hierarchical Transfer Learning Framework for Cross-Domain Fake News Detection
UNITE-FND: Reframing Multimodal Fake News Detection through Unimodal Scene Translation
A Hybrid Transformer Model for Fake News Detection: Leveraging Bayesian Optimization and Bidirectional Recurrent Unit
Neighborhood-Order Learning Graph Attention Network for Fake News Detection
News about Global North considered Truthful! The Geo-political Veracity Gradient in Global South News
Multimodal Inverse Attention Network with Intrinsic Discriminant Feature Exploitation for Fake News Detection
Challenges and Innovations in LLM-Powered Fake News Detection: A Synthesis of Approaches and Future Directions
Fake News Detection After LLM Laundering: Measurement and Explanation
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