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

Yuxia Wang, Jonibek Mansurov, Petar Ivanov, Jinyan Su, Artem Shelmanov +10 more
4/22/2024
cs.CL

No official code found. Best implementation: mbzuai-nlp/SemEval2024-task8 (82 stars, Apache-2.0, last commit 2024-04-22).

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.

View on arXivView PDF

Code Implementations(1)

mbzuai-nlp/SemEval2024-task8Community72%
Apache-2.0

SemEval2024-task8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection

8231Shell, PythonJul 16, 20232 years agoApache-2.0

Similar Papers

TrustAI at SemEval-2024 Task 8: A Comprehensive Analysis of Multi-domain Machine Generated Text Detection Techniques

90% match2024

PetKaz at SemEval-2024 Task 8: Can Linguistics Capture the Specifics of LLM-generated Text?

89% match2024

KInIT at SemEval-2024 Task 8: Fine-tuned LLMs for Multilingual Machine-Generated Text Detection

89% match2 repos222024

Mast Kalandar at SemEval-2024 Task 8: On the Trail of Textual Origins: RoBERTa-BiLSTM Approach to Detect AI-Generated Text

87% match2024

Fine-tuning Large Language Models for Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection

87% match2024

SemEval-2024 Task 8: Weighted Layer Averaging RoBERTa for Black-Box Machine-Generated Text Detection

85% match1 repo2024

Cite this paper

@article{wang2024semeval,
  title  = {SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection},
  author = {Yuxia Wang and Jonibek Mansurov and Petar Ivanov and Jinyan Su and Artem Shelmanov and Akim Tsvigun and Osama Mohammed Afzal and Tarek Mahmoud and Giovanni Puccetti and Thomas Arnold and Chenxi Whitehouse and Alham Fikri Aji and Nizar Habash and Iryna Gurevych and Preslav Nakov},
  year   = {2024},
  eprint = {2404.14183},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.14183v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2404.14183.svg)](https://codeofpaper.com/paper/2404.14183)

Discussion