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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 language | English |
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Journal | Computational Linguistics in the Netherlands Journal |
Volume | 13 |
Pages (from-to) | 233–259 |
Number of pages | 27 |
Publication status | Published - 21 Mar 2024 |
Event | The 33rd Meeting of Computational Linguistics in The Netherlands - Antwerpen, Belgium Duration: 22 Sept 2023 → … https://clin33.uantwerpen.be/ |
Conference
Conference | The 33rd Meeting of Computational Linguistics in The Netherlands |
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Country/Territory | Belgium |
City | Antwerpen |
Period | 22/09/2023 → … |
Internet address |
Keywords
- Large Language Model
- Detection of AI
- Generated Text Detection
- Detection
- NLP
- Generative AI
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Multilingual Modelling for Resource-Poor Languages
Bjerva, J. (PI), Lent, H. C. (Project Participant), Chen, Y. (Project Participant), Ploeger, E. (Project Participant), Fekete, M. R. (Project Participant) & Lavrinovics, E. (Project Participant)
01/09/2022 → 31/08/2025
Project: Research