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GUIDEUnderstanding fake news, misinformation & disinformation

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2024 Controlled Change Dodds · LLMs & generative AI, Platforms, policy & society2024 DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detection Wan et al. · arXiv · LLMs & generative AI, Detection methods2024 Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data Marchal et al. · arXiv · LLMs & generative AI, Platforms, policy & society2024 RAIDAR: Generative AI Detection via Rewriting Mao et al. · ICLR · LLMs & generative AI, Detection methods2024 Advancing Graph Representation Learning with Large Language Models: A Comprehensive Survey of Techniques Mao et al. · arXiv · LLMs & generative AI, Datasets & evaluation2024 TELLER: A Trustworthy Framework For Explainable, Generalizable and Controllable Fake News Detection Liu et al. · arXiv · LLMs & generative AI, Detection methods2024 From Skepticism to Acceptance: Simulating the Attitude Dynamics Toward Fake News Liu et al. · arXiv · Psychology & interventions, LLMs & generative AI2024 Measuring Political Bias in Large Language Models: What Is Said and How It Is Said Bang et al. · arXiv · LLMs & generative AI, Platforms, policy & society2024 Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection Ba et al. · arXiv · Deepfakes & multimodal, Detection methods2024 Can LLM-Generated Misinformation Be Detected? Chen & Shu · ICLR 2024 · LLMs & generative AI, Detection methods2023 A Survey of Large Language Models Zhao et al. · arXiv · LLMs & generative AI2023 Universal and Transferable Adversarial Attacks on Aligned Language Models Zou et al. · arXiv · LLMs & generative AI, Platforms, policy & society2023 How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances Zhang et al. · arXiv · LLMs & generative AI, Datasets & evaluation2023 A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions Wu et al. · arXiv · LLMs & generative AI, Detection methods2023 Jailbroken: How Does LLM Safety Training Fail? Wei et al. · arXiv · LLMs & generative AI, Platforms, policy & society2023 Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity Wang et al. · arXiv · LLMs & generative AI, Fact-checking & verification2023 The Evolution of Distributed Systems for Graph Neural Networks and their Origin in Graph Processing and Deep Learning: A Survey Vatter et al. · arXiv · Spread & networks, Detection methods2023 The Science of Detecting LLM-Generated Texts Tang et al. · arXiv · LLMs & generative AI, Detection methods2023 Adapting Fake News Detection to the Era of Large Language Models Su et al. · arXiv · LLMs & generative AI, Detection methods2023 The Amplification Paradox in Recommender Systems Ribeiro et al. · ICWSM · Spread & networks, Platforms, policy & society2023 The Perils & Promises of Fact-checking with Large Language Models Quelle & Bovet · arXiv · Fact-checking & verification, LLMs & generative AI2023 Engagement, User Satisfaction, and the Amplification of Divisive Content on Social Media Mills et al. · arXiv · Spread & networks, Platforms, policy & society2023 FLIRT: Feedback Loop In-context Red Teaming Mehrabi et al. · arXiv · LLMs & generative AI, Deepfakes & multimodal2023 Disinformation 2.0 in the Age of AI: A Cybersecurity Perspective Mazurczyk et al. · ACM Publication · Platforms, policy & society, LLMs & generative AI