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A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization
March 5, 2024, 2:51 p.m. | Tharindu Kumarage, Garima Agrawal, Paras Sheth, Raha Moraffah, Aman Chadha, Joshua Garland, Huan Liu
cs.CL updates on arXiv.org arxiv.org
Abstract: We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs) capable of generating high-quality text. While these LLMs have revolutionized text generation across various domains, they also pose significant risks to the information ecosystem, such as the potential for generating convincing propaganda, misinformation, and disinformation at scale. This paper offers a review of AI-generated text forensic systems, an emerging field addressing the challenges of LLM misuses. We present an overview of the …
abstract advanced ai-generated text arxiv attribution cs.ai cs.cl detection domains ecosystem generated information language language models large language large language models llms quality risks survey systems text text generation the information type
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