Prompting for multimodal hateful meme classification
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 ext...
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2022
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sg-smu-ink.sis_research-86742023-01-10T03:39:45Z Prompting for multimodal hateful meme classification CAO, Rui LEE, Roy Ka-Wei CHONG, Wen-Haw JIANG, Jing 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. 2022-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/7671 https://ink.library.smu.edu.sg/context/sis_research/article/8674/viewcontent/Prompting_for_multimodal_hateful_meme_classification.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Artificial Intelligence and Robotics Databases and Information Systems Graphics and Human Computer Interfaces |
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Artificial Intelligence and Robotics Databases and Information Systems Graphics and Human Computer Interfaces CAO, Rui LEE, Roy Ka-Wei CHONG, Wen-Haw JIANG, Jing Prompting for multimodal hateful meme classification |
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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. |
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CAO, Rui LEE, Roy Ka-Wei CHONG, Wen-Haw JIANG, Jing |
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CAO, Rui LEE, Roy Ka-Wei CHONG, Wen-Haw JIANG, Jing |
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CAO, Rui |
title |
Prompting for multimodal hateful meme classification |
title_short |
Prompting for multimodal hateful meme classification |
title_full |
Prompting for multimodal hateful meme classification |
title_fullStr |
Prompting for multimodal hateful meme classification |
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Prompting for multimodal hateful meme classification |
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prompting for multimodal hateful meme classification |
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Institutional Knowledge at Singapore Management University |
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2022 |
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https://ink.library.smu.edu.sg/sis_research/7671 https://ink.library.smu.edu.sg/context/sis_research/article/8674/viewcontent/Prompting_for_multimodal_hateful_meme_classification.pdf |
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