Skip to content
GUIDEUnderstanding fake news, misinformation & disinformation

Explore papers

Filter by research area, year and venue. Every filter is in the address bar, so you can share a view as a link.

79 results
CardsList
2026 MMMMM: A Unified Taxonomy for Investigating the Mechanisms of Multilingual MultiModal Misinformation Borenstein et al. · arXiv · Deepfakes & multimodal, Datasets & evaluation2026 Swin Meets EfficientNet: Lightweight Architectures for GAN-Based Face Forensics Basu et al. · arXiv · Deepfakes & multimodal, Detection methods2026 Calibrating Small Language Models for Claim Check-Worthiness Detection Amatya et al. · arXiv · LLMs & generative AI, Fact-checking & verification2026 Build it, Break it, Repeat: Benchmarking and improving LLM-manipulated disinformation detection in social media posts Thomas et al. · arXiv · LLMs & generative AI, Detection methods2026 The GenAI Catch-22: Use of Generative Artificial Intelligence in Norwegian Newsrooms During the 2025 Parliamentary Election Reisjå & Løvtie · arXiv · LLMs & generative AI, Platforms, policy & society2026 Modeling Duelling Contagions of True and False Information in the Face of Inherent Individual biases Krishna et al. · arXiv · Spread & networks, Psychology & interventions2026 Quantifying Political Partisanship for Cross-Platform Analyses Ameen & Healey · arXiv · Spread & networks, Platforms, policy & society2026 Network Information Enhances Unreliable News Domain Detection Kefler et al. · arXiv · Spread & networks, Detection methods2026 From Manipulation to Mistrust: Explaining Diverse Micro-Video Misinformation for Robust Debunking in the Wild Zeng et al. · ACM International Conference · Datasets & evaluation, Deepfakes & multimodal2026 Seeing Through Deception: Uncovering Misleading Creator Intent in Multimodal News with Vision-Language Models Wu et al. · ICLR 2026 · Deepfakes & multimodal, Detection methods2026 Prompt-Induced Linguistic Fingerprints for LLM-Generated Fake News Detection Wang et al. · World Wide Web Conference · LLMs & generative AI, Detection methods2026 MALicious INTent Dataset and Inoculating LLMs for Enhanced Disinformation Detection Modzelewski et al. · arXiv · Datasets & evaluation, LLMs & generative AI2026 Beyond Speculation: Measuring the Growing Presence of LLM-Generated Texts in Multilingual Disinformation Macko et al. · IEEE Computer · LLMs & generative AI, Datasets & evaluation2026 Industrialized Deception: The Collateral Effects of LLM-Generated Misinformation on Digital Ecosystems Loth et al. · ACM Web Conference 2026 · LLMs & generative AI, Detection methods2026 What's Left Unsaid? Detecting and Correcting Misleading Omissions in Multimodal News Previews Li et al. · arXiv · Detection methods, Deepfakes & multimodal2026 Agentic Mixed-Source Multi-Modal Misinformation Detection with Adaptive Test-Time Scaling Jiang et al. · ACM Conference · Deepfakes & multimodal, Detection methods2026 'Your AI Text is not Mine': Redefining and Evaluating AI-generated Text Detection under Realistic Assumptions Dycke et al. · arXiv · LLMs & generative AI, Datasets & evaluation2026 Spectral Analysis of Fake News Propagation Cai & Zafarani · SIAM · Spread & networks, Detection methods2026 The Paradigm Shift: A Comprehensive Survey on Large Vision Language Models for Multimodal Fake News Detection Ai et al. · arXiv · Deepfakes & multimodal, LLMs & generative AI2025 SINcon: Mitigate LLM-Generated Malicious Message Injection Attack for Rumor Detection Zhang et al. · arXiv · LLMs & generative AI, Detection methods2025 Challenges and Innovations in LLM-Powered Fake News Detection: A Synthesis of Approaches and Future Directions Yi et al. · arXiv · LLMs & generative AI, Detection methods2025 Debunk and Infer: Multimodal Fake News Detection via Diffusion-Generated Evidence and LLM Reasoning Yan et al. · arXiv · Deepfakes & multimodal, LLMs & generative AI2025 Bridging Thoughts and Words: Graph-Based Intent-Semantic Joint Learning for Fake News Detection Wang et al. · CIKM · Detection methods, LLMs & generative AI2025 A Guide to Misinformation Detection Data and Evaluation Thibault et al. · KDD '25 — 31st ACM SIGKDD Conference on… · Datasets & evaluation, Detection methods