DUTIR938 at SemEval-2024 Task 4: Semi-Supervised Learning and Model Ensemble for Persuasion Techniques Detection in Memes
Erchen Yu, Junlong Wang, Xuening Qiao, Jiewei Qi, Zhaoqing Li, Hongfei Lin, Linlin Zong, Bo Xu
Abstract
The development of social platforms has facilitated the proliferation of disinformation, with memes becoming one of the most popular types of propaganda for disseminating disinformation on the internet. Effectively detecting the persuasion techniques hidden within memes is helpful in understanding user-generated content and further promoting the detection of disinformation on the internet. This paper demonstrates the approach proposed by Team DUTIR938 in Subtask 2b of SemEval-2024 Task 4. We propose a dual-channel model based on semi-supervised learning and model ensemble. We utilize CLIP to extract image features, and employ various pretrained language models under task-adaptive pretraining for text feature extraction. To enhance the detection and generalization capabilities of the model, we implement sample data augmentation using semi-supervised pseudo-labeling methods, introduce adversarial training strategies, and design a two-stage global model ensemble strategy. Our proposed method surpasses the provided baseline method, with Macro/Micro F1 values of 0.80910/0.83667 in the English leaderboard. Our submission ranks 3rd/19 in terms of Macro F1 and 1st/19 in terms of Micro F1.- Anthology ID:
- 2024.semeval-1.94
- 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:
- 642–648
- Language:
- URL:
- https://aclanthology.org/2024.semeval-1.94
- DOI:
- 10.18653/v1/2024.semeval-1.94
- Cite (ACL):
- Erchen Yu, Junlong Wang, Xuening Qiao, Jiewei Qi, Zhaoqing Li, Hongfei Lin, Linlin Zong, and Bo Xu. 2024. DUTIR938 at SemEval-2024 Task 4: Semi-Supervised Learning and Model Ensemble for Persuasion Techniques Detection in Memes. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 642–648, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- DUTIR938 at SemEval-2024 Task 4: Semi-Supervised Learning and Model Ensemble for Persuasion Techniques Detection in Memes (Yu et al., SemEval 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.semeval-1.94.pdf