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.

61 results
CardsList
2026 VeriSpoof: Beyond Real or Fake with One Audio LLM Xiao & Dang · Technical Report · Deepfakes & multimodal, Detection methods2026 DeepfakeGenome: Toward Next-Generation Deepfake Attribution Wang et al. · NeurIPS 2026 · Deepfakes & multimodal, Datasets & evaluation2026 UniGADD: Universal Generator-Agnostic Deepfake Detector Tomczyk et al. · arXiv · Deepfakes & multimodal, Detection methods2026 CLRM: Cross-Layer Relation Modeling for Audio Deepfake Detection Qu et al. · arXiv · Deepfakes & multimodal, Detection methods2026 GraphSeal: Graph-Augmented Speech Deepfake Detection via Temporal-Spectral Artifact Propagation Lee et al. · arXiv · Deepfakes & multimodal, Detection methods2026 ReplayFactor: Replay-Aware Dual-Attribute Learning for Practical Speech Deepfake Detection He et al. · arXiv · Deepfakes & multimodal, Detection methods2026 Detector-Guided Vocoder Training for Adversarial Text-to-Speech Synthesis Cui et al. · arXiv · Deepfakes & multimodal, LLMs & generative AI2026 Drowning in AI Slop: How Social Media Platforms (Do Not) Label AI and Deepfake Content under EU law Rijsbosch et al. · arXiv · Platforms, policy & society, Deepfakes & multimodal2026 To Trust or Not to Trust: Retrieval-Augmented Fact Checking in Speech Mazumder et al. · arXiv · Fact-checking & verification, LLMs & generative AI2026 VietPrism: A Large-Scale Vietnamese Speech and Deepfake Corpus with Diverse Dialects and Code-Switching Hoang & Le · arXiv · Deepfakes & multimodal, Datasets & evaluation2026 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 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 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 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 Debunk and Infer: Multimodal Fake News Detection via Diffusion-Generated Evidence and LLM Reasoning Yan et al. · arXiv · Deepfakes & multimodal, LLMs & generative AI2025 VLDBench: Evaluating Multimodal Disinformation with Regulatory Alignment Raza et al. · arXiv · Deepfakes & multimodal, Datasets & evaluation2025 E-FreeM2: Efficient Training-Free Multi-Scale and Cross-Modal News Verification via MLLMs Phan et al. · SCID '25 · LLMs & generative AI, Detection methods2025 Synergizing LLMs with Global Label Propagation for Multimodal Fake News Detection Hu et al. · arXiv · Deepfakes & multimodal, LLMs & generative AI2024 Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection Ba et al. · arXiv · Deepfakes & multimodal, Detection methods2023 FLIRT: Feedback Loop In-context Red Teaming Mehrabi et al. · arXiv · LLMs & generative AI, Deepfakes & multimodal