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arXiv · 2404.14183

SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection

Yuxia Wang·Jonibek Mansurov·Petar Ivanov·Jinyan Su·Artem Shelmanov·Akim Tsvigun·Osama Mohammed Afzal·Tarek Mahmoud·Giovanni Puccetti·Thomas Arnold·Chenxi Whitehouse·Alham Fikri Aji·Nizar Habash·Iryna Gurevych·Preslav Nakov
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Abstract

We present the results and the main findings of SemEval-2024 Task 8: Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection. The task featured three subtasks. Subtask A is a binary classification task determining whether a text is written by a human or generated by a machine. This subtask has two tracks: a monolingual track focused solely on English texts and a multilingual track. Subtask B is to detect the exact source of a text, discerning whether it is written by a human or generated by a specific LLM. Subtask C aims to identify the changing point within a text, at which the authorship transitions from human to machine. The task attracted a large number of participants: subtask A monolingual (126), subtask A multilingual (59), subtask B (70), and subtask C (30). In this paper, we present the task, analyze the results, and discuss the system submissions and the methods they used. For all subtasks, the best systems used LLMs.

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Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov, Akim Tsvigun, Osama Mohammed Afzal, Tarek Mahmoud, Giovanni Puccetti, Thomas Arnold, Chenxi Whitehouse, Alham Fikri Aji, Nizar Habash, Iryna Gurevych, Preslav Nakov. 2024-04-22. SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection. https://arxiv.org/abs/2404.14183

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