KInIT at SemEval-2024 Task 8: Fine-tuned LLMs for Multilingual Machine-Generated Text Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F24%3A00137352" target="_blank" >RIV/00216224:14330/24:00137352 - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2024.semeval-1.84/" target="_blank" >https://aclanthology.org/2024.semeval-1.84/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.18653/v1/2024.semeval-1.84" target="_blank" >10.18653/v1/2024.semeval-1.84</a>
Alternative languages
Result language
angličtina
Original language name
KInIT at SemEval-2024 Task 8: Fine-tuned LLMs for Multilingual Machine-Generated Text Detection
Original language description
SemEval-2024 Task 8 is focused on multigenerator, multidomain, and multilingual black-box machine-generated text detection. Such a detection is important for preventing a potential misuse of large language models (LLMs), the newest of which are very capable in generating multilingual human-like texts. We have coped with this task in multiple ways, utilizing language identification and parameter-efficient fine-tuning of smaller LLMs for text classification. We have further used the per-language classification-threshold calibration to uniquely combine fine-tuned models predictions with statistical detection metrics to improve generalization of the system detection performance. Our submitted method achieved competitive results, ranking at the fourth place, just under 1 percentage point behind the winner.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
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
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
ISBN
9798891761070
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
558-564
Publisher name
Association for Computational Linguistics
Place of publication
Mexico City, Mexico
Event location
Mexico City, Mexico
Event date
Jan 1, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001356736800084