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HANSEN: Human and AI Spoken Text Benchmark for Authorship Analysis.

, , , , , and . EMNLP (Findings), page 13706-13724. Association for Computational Linguistics, (2023)

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Characterizing Man-made vs. Machine-made Chatbot Dialogs., , , , and . TTO, (2019)HANSEN: Human and AI Spoken Text Benchmark for Authorship Analysis., , , , , and . EMNLP (Findings), page 13706-13724. Association for Computational Linguistics, (2023)Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspective., , and . CoRR, (2022)GPT-who: An Information Density-based Machine-Generated Text Detector., , and . CoRR, (2023)Robustness of Bayesian Neural Networks to White-Box Adversarial Attacks., , , and . AIKE, page 72-80. IEEE, (2021)TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation., , , , and . EMNLP (Findings), page 2001-2016. Association for Computational Linguistics, (2021)Authorship Attribution for Neural Text Generation., , , and . EMNLP (1), page 8384-8395. Association for Computational Linguistics, (2020)Authorship Obfuscation in Multilingual Machine-Generated Text Detection., , , , , , , , , and . CoRR, (2024)Understanding Individual and Team-based Human Factors in Detecting Deepfake Texts., , , , , and . CoRR, (2023)Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspective., , and . SIGKDD Explor., 25 (1): 1-18 (2023)