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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AP8Z6TEQP" target="_blank" >RIV/00216208:11320/25:P8Z6TEQP - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197756038&partnerID=40&md5=335c82eb755bb3ee34f722b00d55c3ad" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197756038&partnerID=40&md5=335c82eb755bb3ee34f722b00d55c3ad</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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. © 2024 Pieter Fivez et al.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Comput. Linguist. Netherlands J.

  • ISBN

  • ISSN

    2211-4009

  • e-ISSN

  • Number of pages

    27

  • Pages from-to

    233-259

  • Publisher name

    Computational Linguistics in the Netherlands

  • Place of publication

  • Event location

    Antwerp

  • Event date

    Jan 1, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article