Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
12-2022
Abstract
Hateful meme classification is a challenging multimodal task that requires complex reasoning and contextual background knowledge. Ideally, we could leverage an explicit external knowledge base to supplement contextual and cultural information in hateful memes. However, there is no known explicit external knowledge base that could provide such hate speech contextual information. To address this gap, we propose PromptHate, a simple yet effective prompt-based model that prompts pre-trained language models (PLMs) for hateful meme classification. Specifically, we construct simple prompts and provide a few in-context examples to exploit the implicit knowledge in the pretrained RoBERTa language model for hateful meme classification. We conduct extensive experiments on two publicly available hateful and offensive meme datasets. Our experimental results show that PromptHate is able to achieve a high AUC of 90.96, outperforming state-ofthe-art baselines on the hateful meme classification task. We also perform fine-grained analyses and case studies on various prompt settings and demonstrate the effectiveness of the prompts on hateful meme classification.
Discipline
Artificial Intelligence and Robotics | Databases and Information Systems | Graphics and Human Computer Interfaces
Research Areas
Data Science and Engineering; Information Systems and Management; Intelligent Systems and Optimization
Publication
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
City or Country
Abu Dhabi, UAE
Citation
CAO, Rui; LEE, Roy Ka-Wei; CHONG, Wen-Haw; and JIANG, Jing.
Prompting for multimodal hateful meme classification. (2022). Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing.
Available at: https://ink.library.smu.edu.sg/sis_research/7671
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Artificial Intelligence and Robotics Commons, Databases and Information Systems Commons, Graphics and Human Computer Interfaces Commons