The CLIN33 Shared Task on the Detection of Text Generated by Large Language Models

Pieter Fivez, Walter Daelemans, Tim Van de Cruys, Yury Kashnitsky, Savvas Chamezopoulos, Hadi Mohammadi, Anastasia Giachanou, Ayoub Bagheri, Wessel Poelman, Juraj Vladika, Esther Ploeger, Johannes Bjerva, Florian Matthes, Hans van Halteren

Research output: Contribution to journalConference article in JournalResearchpeer-review

3 Citations (Scopus)

Abstract

The Shared Task for CLIN33 focuses on a relatively novel yet societally relevant task: the detection of text generated by Large Language Models (LLMs). We frame this detection task as a binary classification problem (LLM-generated or not), using test data from up to 6 different domains and text genres for both Dutch and English. Part of this test data was held out entirely from the contestants, including a ”mystery genre” which belonged to an unknown domain (later revealed to be columns). Four teams submitted 11 runs with substantially different models and features. This paper gives an overview of our task setup and contains the evaluation and detailed descriptions of the participating systems. Notably, included in the winning systems are both deep learning models as well as more traditional machine learning models leveraging task-specific feature engineering.
Original languageEnglish
JournalComputational Linguistics in the Netherlands Journal
Volume13
Pages (from-to)233–259
Number of pages27
Publication statusPublished - 21 Mar 2024
EventThe 33rd Meeting of Computational Linguistics in The Netherlands - Antwerpen, Belgium
Duration: 22 Sept 2023 → …
https://clin33.uantwerpen.be/

Conference

ConferenceThe 33rd Meeting of Computational Linguistics in The Netherlands
Country/TerritoryBelgium
CityAntwerpen
Period22/09/2023 → …
Internet address

Keywords

  • Large Language Model
  • Detection of AI
  • Generated Text Detection
  • Detection
  • NLP
  • Generative AI

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