KInITVeraAI at SemEval-2023 Task 3: Simple yet Powerful Multilingual Fine-Tuning for Persuasion Techniques Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F23%3APU149533" target="_blank" >RIV/00216305:26230/23:PU149533 - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2023.semeval-1.86/" target="_blank" >https://aclanthology.org/2023.semeval-1.86/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.18653/v1/2023.semeval-1.86" target="_blank" >10.18653/v1/2023.semeval-1.86</a>
Alternative languages
Result language
angličtina
Original language name
KInITVeraAI at SemEval-2023 Task 3: Simple yet Powerful Multilingual Fine-Tuning for Persuasion Techniques Detection
Original language description
This paper presents the best-performing solution to the SemEval 2023 Task 3 on the subtask 3 dedicated to persuasion techniques detection. Due to a high multilingual character of the input data and a large number of 23 predicted labels (causing a lack of labelled data for some language-label combinations), we opted for fine-tuning pre-trained transformer-based language models. Conducting multiple experiments, we find the best configuration, which consists of large multilingual model (XLM-RoBERTa large) trained jointly on all input data, with carefully calibrated confidence thresholds for seen and surprise languages separately. Our final system performed the best on 6 out of 9 languages (including two surprise languages) and achieved highly competitive results on the remaining three languages.
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
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
17th International Workshop on Semantic Evaluation, SemEval 2023 - Proceedings of the Workshop
ISBN
978-1-959429-99-9
ISSN
—
e-ISSN
—
Number of pages
9
Pages from-to
629-637
Publisher name
Association for Computational Linguistics
Place of publication
Toronto
Event location
Toronto
Event date
Jul 9, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—