2024.acl-tutorials.6@ACL

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#1 Detecting Machine-Generated Text: Techniques and Challenges [PDF2] [Copy] [Kimi1] [REL]

Authors: Li Gao ; Wenhan Xiong ; Taewoo Kim

As AI-generated text increasingly resembles human-written content, the ability to detect machine-generated text becomes crucial in many applications. This tutorial aims to provide a comprehensive overview of text detection techniques, focusing on machine-generated text and deepfakes. We will discuss various methods for distinguishing between human-written and machine-generated text, including statistical methods, neural network-based techniques, and hybrid approaches. The tutorial will also cover the challenges in the detection process, such as dealing with evolving models and maintaining robustness against adversarial attacks. By the end of the session, attendees will have a solid understanding of current techniques and future directions in the field of text detection.