Overview of AuTexTification at IberLEF 2023: Detection and Attribution of Machine-Generated Text in Multiple Domains

• URL: http://arxiv.org/abs/2309.11285v1
• Date: Wed, 20 Sep 2023 13:10:06 GMT
• Title: Overview of AuTexTification at IberLEF 2023: Detection and Attribution of Machine-Generated Text in Multiple Domains
• Authors: Areg Mikael Sarvazyan, Jos\'e \'Angel Gonz\'alez, Marc Franco-Salvador, Francisco Rangel, Berta Chulvi, Paolo Rosso
• Abstract summary: This paper presents the overview of the AuTexTification task as part of the IberLEF 2023 Workshop in Iberian Languages Evaluation Forum. Our AuTexTification dataset contains more than 160.000 texts across two languages (English and Spanish) and five domains (tweets, reviews, news, legal, and how-to articles) A total of 114 teams signed up to participate, of which 36 sent 175 runs, and 20 of them sent their working notes.
• Score: 6.44756483013808
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: This paper presents the overview of the AuTexTification shared task as part of the IberLEF 2023 Workshop in Iberian Languages Evaluation Forum, within the framework of the SEPLN 2023 conference. AuTexTification consists of two subtasks: for Subtask 1, participants had to determine whether a text is human-authored or has been generated by a large language model. For Subtask 2, participants had to attribute a machine-generated text to one of six different text generation models. Our AuTexTification 2023 dataset contains more than 160.000 texts across two languages (English and Spanish) and five domains (tweets, reviews, news, legal, and how-to articles). A total of 114 teams signed up to participate, of which 36 sent 175 runs, and 20 of them sent their working notes. In this overview, we present the AuTexTification dataset and task, the submitted participating systems, and the results.

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