LomonosovMSU at SemEval-2024 Task 4: Comparing LLMs and embedder models to identifying propaganda techniques in the content of memes in English for subtasks No1, No2a, and No2b

Gleb Skiba, Mikhail Pukemo, Dmitry Melikhov, Konstantin Vorontsov


Abstract
This paper presents the solution of the LomonosovMSU team for the SemEval-2024 Task 4 “Multilingual Detection of Persuasion Techniques in Memes” competition for the English language task. During the task solving process, generative and BERT-like (training classifiers on top of embedder models) approaches were tested for subtask No1, as well as an BERT-like approach on top of multimodal embedder models for subtasks No2a/No2b. The models were trained using datasets provided by the competition organizers, enriched with filtered datasets from previous SemEval competitions. The following results were achieved: 18th place for subtask No1, 9th place for subtask No2a, and 11th place for subtask No2b.
Anthology ID:
2024.semeval-1.221
Volume:
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1544–1548
Language:
URL:
https://aclanthology.org/2024.semeval-1.221
DOI:
10.18653/v1/2024.semeval-1.221
Bibkey:
Cite (ACL):
Gleb Skiba, Mikhail Pukemo, Dmitry Melikhov, and Konstantin Vorontsov. 2024. LomonosovMSU at SemEval-2024 Task 4: Comparing LLMs and embedder models to identifying propaganda techniques in the content of memes in English for subtasks No1, No2a, and No2b. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 1544–1548, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
LomonosovMSU at SemEval-2024 Task 4: Comparing LLMs and embedder models to identifying propaganda techniques in the content of memes in English for subtasks No1, No2a, and No2b (Skiba et al., SemEval 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.semeval-1.221.pdf
Supplementary material:
 2024.semeval-1.221.SupplementaryMaterial.zip
Supplementary material:
 2024.semeval-1.221.SupplementaryMaterial.txt