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2026
VeriSpoof: Beyond Real or Fake with One Audio LLM
Xiao & Dang · Technical Report · Deepfakes & multimodal, Detection methods2026
VEX-Bench: Benchmarking Verification Complexity of LLM-Generated Misinformation
Huang et al. · NeurIPS 2026, Track on Evaluations and Datasets · LLMs & generative AI, Fact-checking & verification2026
Prompt-Induced Linguistic Fingerprints for LLM-Generated Fake News Detection
Wang et al. · World Wide Web Conference · LLMs & generative AI, Detection methods2026
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
Agentic Mixed-Source Multi-Modal Misinformation Detection with Adaptive Test-Time Scaling
Jiang et al. · ACM Conference · Deepfakes & multimodal, Detection methods2025
Bridging Thoughts and Words: Graph-Based Intent-Semantic Joint Learning for Fake News Detection
Wang et al. · CIKM · Detection methods, LLMs & generative AI2025
E-FreeM2: Efficient Training-Free Multi-Scale and Cross-Modal News Verification via MLLMs
Phan et al. · SCID '25 · LLMs & generative AI, Detection methods2025
Propasafe: A BERT-based offline tool for propaganda detection
Sharma et al. · ACM Web Conference 2025 · Detection methods, LLMs & generative AI2024
RAIDAR: Generative AI Detection via Rewriting
Mao et al. · ICLR · LLMs & generative AI, Detection methods2024
Can LLM-Generated Misinformation Be Detected?
Chen & Shu · ICLR 2024 · LLMs & generative AI, Detection methods2023
The Amplification Paradox in Recommender Systems
Ribeiro et al. · ICWSM · Spread & networks, Platforms, policy & society2023
Disinformation 2.0 in the Age of AI: A Cybersecurity Perspective
Mazurczyk et al. · ACM Publication · Platforms, policy & society, LLMs & generative AI2023
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Dai et al. · ACM Computing Surveys · LLMs & generative AI, Detection methods2023
A Survey on Evaluation of Large Language Models
Chang et al. · Journal of the ACM · LLMs & generative AI, Datasets & evaluation2023
A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT
Cao et al. · J. ACM, Vol. 37, No. 4 · LLMs & generative AI, Deepfakes & multimodal2023
The Looming Threat of Fake and LLM-generated LinkedIn Profiles: Challenges and Opportunities for Detection and Prevention
Ayoobi et al. · 3rd ACM Conference on Hypertext and Social Media · LLMs & generative AI, Datasets & evaluation2023
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature
Mitchell et al. · 40th International Conference on Machine… · LLMs & generative AI, Detection methods2022
All the News That's Fit to Fabricate: AI-Generated Text as a Tool of Media Misinformation
Kreps et al. · Journal of Experimental Political Science · LLMs & generative AI, Detection methods2022
A Comprehensive Survey on Trustworthy Recommender Systems
Fan et al. · ACM Computing Surveys · Platforms, policy & society, Detection methods2021
Multimodal Emergent Fake News Detection via Meta Neural Process Networks
Wang et al. · ACM SIGKDD Conference on Knowledge Discovery… · Deepfakes & multimodal, Detection methods2021
MDFEND: Multi-domain Fake News Detection
Nan et al. · CIKM '21: The 30th ACM International… · Detection methods, Datasets & evaluation2021
The Threat of Offensive AI to Organizations
Mirsky et al. · ACM Computing Surveys · Platforms, policy & society, Bots & coordinated campaigns2021
DEAP-FAKED: Knowledge Graph based Approach for Fake News Detection
Mayank et al. · IEEE/ACM International Conference on Advances… · Detection methods, Datasets & evaluation