@inproceedings{wang-etal-2024-semeval-2024,
title = "{S}em{E}val-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection",
author = "Wang, Yuxia and
Mansurov, Jonibek and
Ivanov, Petar and
Su, Jinyan and
Shelmanov, Artem and
Tsvigun, Akim and
Mohammed Afzal, Osama and
Mahmoud, Tarek and
Puccetti, Giovanni and
Arnold, Thomas",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Tayyar Madabushi, Harish and
Da San Martino, Giovanni and
Rosenthal, Sara and
Ros{\'a}, Aiala},
booktitle = "Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.semeval-1.279",
doi = "10.18653/v1/2024.semeval-1.279",
pages = "2057--2079",
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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%0 Conference Proceedings
%T SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection
%A Wang, Yuxia
%A Mansurov, Jonibek
%A Ivanov, Petar
%A Su, Jinyan
%A Shelmanov, Artem
%A Tsvigun, Akim
%A Mohammed Afzal, Osama
%A Mahmoud, Tarek
%A Puccetti, Giovanni
%A Arnold, Thomas
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Tayyar Madabushi, Harish
%Y Da San Martino, Giovanni
%Y Rosenthal, Sara
%Y Rosá, Aiala
%S Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F wang-etal-2024-semeval-2024
%X 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.
%R 10.18653/v1/2024.semeval-1.279
%U https://aclanthology.org/2024.semeval-1.279
%U https://doi.org/10.18653/v1/2024.semeval-1.279
%P 2057-2079
Markdown (Informal)
[SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection](https://aclanthology.org/2024.semeval-1.279) (Wang et al., SemEval 2024)
ACL
- Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov, Akim Tsvigun, Osama Mohammed Afzal, Tarek Mahmoud, Giovanni Puccetti, and Thomas Arnold. 2024. SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 2057–2079, Mexico City, Mexico. Association for Computational Linguistics.