Detecting Harmful Memes and Their Targets-Reference-Cited by-同舟云学术

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Detecting Harmful Memes and Their Targets

Published:2021 Issue: Volume: Page:
ISSN:
Container-title:Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
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Author:

Pramanick Shraman,Dimitrov Dimitar,Mukherjee Rituparna,Sharma Shivam,Akhtar Md. Shad,Nakov Preslav,Chakraborty Tanmoy

Publisher

Association for Computational Linguistics

Cited by 37 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Emotion-Aware Multimodal Fusion for Meme Emotion Detection;IEEE Transactions on Affective Computing;2024-07

2. AISG's Online Safety Prize Challenge: Detecting Harmful Social Bias in Multimodal Memes;Companion Proceedings of the ACM Web Conference 2024;2024-05-13

3. RUHate-MM: Identification of Hate Speech and Targets using Multimodal Data from Russia-Ukraine Crisis;Companion Proceedings of the ACM Web Conference 2024;2024-05-13

4. Understanding (Dark) Humour with Internet Meme Analysis;Companion Proceedings of the ACM Web Conference 2024;2024-05-13

5. Modularized Networks for Few-shot Hateful Meme Detection;Proceedings of the ACM Web Conference 2024;2024-05-13

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