Overview of the 2023 ALTA Shared Task: discriminate between human-written and machine-generated text

Diego Molla; Haolan Zhan; Xuanli He; Qiongkai Xu

Overview of the 2023 ALTA Shared Task: discriminate between human-written and machine-generated text

Diego Molla, Haolan Zhan, Xuanli He, Qiongkai Xu

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

13 Citations (Scopus)

Abstract

The ALTA shared tasks have been running annually since 2010. In 2023, the purpose of the task is to build automatic detection systems that can discriminate between human-written and synthetic text generated by Large Language Models (LLM). In this paper we present the task, the evaluation criteria, and the results of the systems participating in the shared task.

Original language	English
Title of host publication	Proceedings of the 21st AnnualWorkshop of the Australasian Language Technology Association
Place of Publication	Online
Publisher	Association for Computational Linguistics
Pages	148-152
Number of pages	5
Publication status	Published - 2023
Event	21st Annual Workshop of the Australasian Language Technology Association, ALTA 2023 - Melbourne, Australia Duration: 29 Nov 2023 → 1 Dec 2023

Conference

Conference	21st Annual Workshop of the Australasian Language Technology Association, ALTA 2023
Country/Territory	Australia
City	Melbourne
Period	29/11/23 → 1/12/23

Access to Document

https://aclanthology.org/2023.alta-1.17Licence: Unspecified

Cite this

@inproceedings{5c8f9f1360f04be597054ade13f09256,

title = "Overview of the 2023 ALTA Shared Task: discriminate between human-written and machine-generated text",

abstract = "The ALTA shared tasks have been running annually since 2010. In 2023, the purpose of the task is to build automatic detection systems that can discriminate between human-written and synthetic text generated by Large Language Models (LLM). In this paper we present the task, the evaluation criteria, and the results of the systems participating in the shared task.",

author = "Diego Molla and Haolan Zhan and Xuanli He and Qiongkai Xu",

year = "2023",

language = "English",

pages = "148--152",

booktitle = "Proceedings of the 21st AnnualWorkshop of the Australasian Language Technology Association",

publisher = "Association for Computational Linguistics",

address = "United States",

note = "21st Annual Workshop of the Australasian Language Technology Association, ALTA 2023 ; Conference date: 29-11-2023 Through 01-12-2023",

}

Molla, D, Zhan, H, He, X & Xu, Q 2023, Overview of the 2023 ALTA Shared Task: discriminate between human-written and machine-generated text. in Proceedings of the 21st AnnualWorkshop of the Australasian Language Technology Association. Association for Computational Linguistics, Online, pp. 148-152, 21st Annual Workshop of the Australasian Language Technology Association, ALTA 2023, Melbourne, Australia, 29/11/23. <https://aclanthology.org/2023.alta-1.17>

Overview of the 2023 ALTA Shared Task: discriminate between human-written and machine-generated text. / Molla, Diego; Zhan, Haolan; He, Xuanli et al.
Proceedings of the 21st AnnualWorkshop of the Australasian Language Technology Association. Online: Association for Computational Linguistics, 2023. p. 148-152.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

TY - GEN

T1 - Overview of the 2023 ALTA Shared Task

T2 - 21st Annual Workshop of the Australasian Language Technology Association, ALTA 2023

AU - Molla, Diego

AU - Zhan, Haolan

AU - He, Xuanli

AU - Xu, Qiongkai

PY - 2023

Y1 - 2023

N2 - The ALTA shared tasks have been running annually since 2010. In 2023, the purpose of the task is to build automatic detection systems that can discriminate between human-written and synthetic text generated by Large Language Models (LLM). In this paper we present the task, the evaluation criteria, and the results of the systems participating in the shared task.

AB - The ALTA shared tasks have been running annually since 2010. In 2023, the purpose of the task is to build automatic detection systems that can discriminate between human-written and synthetic text generated by Large Language Models (LLM). In this paper we present the task, the evaluation criteria, and the results of the systems participating in the shared task.

UR - https://www.scopus.com/pages/publications/85176000114

M3 - Conference proceeding contribution

AN - SCOPUS:85176000114

SP - 148

EP - 152

BT - Proceedings of the 21st AnnualWorkshop of the Australasian Language Technology Association

PB - Association for Computational Linguistics

CY - Online

Y2 - 29 November 2023 through 1 December 2023

ER -

Overview of the 2023 ALTA Shared Task: discriminate between human-written and machine-generated text

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