Cover Image

MegaFake: A Theory-Driven Dataset of Fake News Generated by Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Lionel Z., Ng, Ka Chung, Ma, Yiming, Fan, Wenqi
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adapting Fake News Detection to the Era of Large Language Models
by: Su, Jinyan, et al.
Published: (2023)

Each Fake News is Fake in its Own Way: An Attribution Multi-Granularity Benchmark for Multimodal Fake News Detection
by: Guo, Hao, et al.
Published: (2024)

Heterogeneous Subgraph Transformer for Fake News Detection
by: Zhang, Yuchen, et al.
Published: (2024)

Large Language Model Agent for Fake News Detection
by: Li, Xinyi, et al.
Published: (2024)

FineFake: A Knowledge-Enriched Dataset for Fine-Grained Multi-Domain Fake News Detection
by: Zhou, Ziyi, et al.
Published: (2024)

Fake News Detection and Manipulation Reasoning via Large Vision-Language Models
by: Jin, Ruihan, et al.
Published: (2024)

From Deception to Detection: The Dual Roles of Large Language Models in Fake News
by: Sallami, Dorsaf, et al.
Published: (2024)

Adversarial Style Augmentation via Large Language Model for Robust Fake News Detection
by: Park, Sungwon, et al.
Published: (2024)

Evaluating the Efficacy of Large Language Models in Detecting Fake News: A Comparative Analysis
by: Koka, Sahas, et al.
Published: (2024)

Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data
by: Raza, Shaina, et al.
Published: (2024)

Ax-to-Grind Urdu: Benchmark Dataset for Urdu Fake News Detection
by: Harris, Sheetal, et al.
Published: (2024)

Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detection
by: Hu, Beizhe, et al.
Published: (2023)

MCFEND: A Multi-source Benchmark Dataset for Chinese Fake News Detection
by: Li, Yupeng, et al.
Published: (2024)

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection
by: Zhou, Ziyi, et al.
Published: (2025)

Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors
by: Li, Guanghua, et al.
Published: (2024)

Breaking the Fake News Barrier: Deep Learning Approaches in Bangla Language
by: Mondal, Pronoy Kumar, et al.
Published: (2025)

Large Visual-Language Models Are Also Good Classifiers: A Study of In-Context Multimodal Fake News Detection
by: Jiang, Ye, et al.
Published: (2024)

A Graph-Enhanced Defense Framework for Explainable Fake News Detection with LLM
by: Wang, Bo, et al.
Published: (2026)

Fake Alignment: Are LLMs Really Aligned Well?
by: Wang, Yixu, et al.
Published: (2023)

LiveFact: A Dynamic, Time-Aware Benchmark for LLM-Driven Fake News Detection
by: Xu, Cheng, et al.
Published: (2026)

Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities
by: Yu, Xiaomin, et al.
Published: (2024)

Exposing and Explaining Fake News On-the-Fly
by: de Arriba-Pérez, Francisco, et al.
Published: (2024)

Multi-view autoencoders for Fake News Detection
by: Pereira, Ingryd V. S. T., et al.
Published: (2025)

AMPLE: Emotion-Aware Multimodal Fusion Prompt Learning for Fake News Detection
by: Xu, Xiaoman, et al.
Published: (2024)

Value-Conflict Diagnostics Reveal Widespread Alignment Faking in Language Models
by: Nair, Inderjeet, et al.
Published: (2026)

Seeing Through AI's Lens: Enhancing Human Skepticism Towards LLM-Generated Fake News
by: Ayoobi, Navid, et al.
Published: (2024)

FactGuard: Event-Centric and Commonsense-Guided Fake News Detection
by: He, Jing, et al.
Published: (2025)

Towards Real-Time Fake News Detection under Evidence Scarcity
by: Wei, Guangyu, et al.
Published: (2025)

Out-of-distribution Evidence-aware Fake News Detection via Dual Adversarial Debiasing
by: Liu, Qiang, et al.
Published: (2023)

FaKnow: A Unified Library for Fake News Detection
by: Zhu, Yiyuan, et al.
Published: (2024)

Style-News: Incorporating Stylized News Generation and Adversarial Verification for Neural Fake News Detection
by: Wang, Wei-Yao, et al.
Published: (2024)

External Reliable Information-enhanced Multimodal Contrastive Learning for Fake News Detection
by: Cao, Biwei, et al.
Published: (2025)

Is LLMs Hallucination Usable? LLM-based Negative Reasoning for Fake News Detection
by: Zhang, Chaowei, et al.
Published: (2025)

Cross-Modal Augmentation for Few-Shot Multimodal Fake News Detection
by: Jiang, Ye, et al.
Published: (2024)

Blessing or curse? A survey on the Impact of Generative AI on Fake News
by: Loth, Alexander, et al.
Published: (2024)

Improved Personalized Headline Generation via Denoising Fake Interests from Implicit Feedback
by: Liu, Kejin, et al.
Published: (2025)

FakeGPT: Fake News Generation, Explanation and Detection of Large Language Models
by: Huang, Yue, et al.
Published: (2023)

SocialNLP Fake-EmoReact 2021 Challenge Overview: Predicting Fake Tweets from Their Replies and GIFs
by: Huang, Chien-Kun, et al.
Published: (2024)

MSynFD: Multi-hop Syntax aware Fake News Detection
by: Xiao, Liang, et al.
Published: (2024)

PCoT: Persuasion-Augmented Chain of Thought for Detecting Fake News and Social Media Disinformation
by: Modzelewski, Arkadiusz, et al.
Published: (2025)