Abstract
We describe our approach for SemEval-2021 task 6 on detection of persuasion techniques in multimodal content (memes). Our system combines pretrained multimodal models (CLIP) and chained classifiers. Also, we propose to enrich the data by a data augmentation technique. Our submission achieves a rank of 8/16 in terms of F1-micro and 9/16 with F1-macro on the test set.- Anthology ID:
- 2021.semeval-1.139
- Volume:
- Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Editors:
- Alexis Palmer, Nathan Schneider, Natalie Schluter, Guy Emerson, Aurelie Herbelot, Xiaodan Zhu
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1015–1019
- Language:
- URL:
- https://aclanthology.org/2021.semeval-1.139
- DOI:
- 10.18653/v1/2021.semeval-1.139
- Cite (ACL):
- Erfan Ghadery, Damien Sileo, and Marie-Francine Moens. 2021. LIIR at SemEval-2021 task 6: Detection of Persuasion Techniques In Texts and Images using CLIP features. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 1015–1019, Online. Association for Computational Linguistics.
- Cite (Informal):
- LIIR at SemEval-2021 task 6: Detection of Persuasion Techniques In Texts and Images using CLIP features (Ghadery et al., SemEval 2021)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2021.semeval-1.139.pdf