SemEval-2024 task 8: multidomain, multimodel and multilingual machine-generated text detection
Wang Y., Mansurov J., Ivanov P., Su J., Shelmanov A., Tsvigun A., Afzal O. M., Mahmoud T., Puccetti G., Arnold T., Whitehouse C., Aji A. F., Habash N., Gurevych I., Nakov P.
Machine generated text detection
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.
Back to previous page
@inproceedings{oai:iris.cnr.it:20.500.14243/532501,
title = {SemEval-2024 task 8: multidomain, multimodel and multilingual machine-generated text detection},
author = {Wang Y. and Mansurov J. and Ivanov P. and Su J. and Shelmanov A. and Tsvigun A. and Afzal O. M. and Mahmoud T. and Puccetti G. and Arnold T. and Whitehouse C. and Aji A. F. and Habash N. and Gurevych I. and Nakov P.},
year = {2024}
}