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2024
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
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 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
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 AI2023
Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models' Alignment
Liu et al. · arXiv · LLMs & generative AI, Platforms, policy & society2023
Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations
Goldstein et al. · arXiv · LLMs & generative AI, Platforms, policy & society2023
Toxicity in ChatGPT: Analyzing Persona-assigned Language Models
Deshpande et al. · arXiv · LLMs & generative AI, Platforms, policy & society2023
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 & multimodal