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While significant progress has been made using machine learning algorithms to detect hate speech, important technical challenges still remain to be solved in order to bring their performance closer to human accuracy.
Are we pretraining it right? digging deeper into visio-linguistic pretraining, 2020
Amanpreet Singh, Vedanuj Goswami, and Devi Parikh · 2004
Earlier work this paper cites.
The hateful memes challenge: Detecting hate speech in multimodal memes, 2020
Douwe Kiela, Hamed Firooz, Aravind Mohan, Vedanuj Goswami, Amanpreet Singh, Pratik Ringshia, and Davide Testuggine · 2005
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Luowei Zhou, Hamid Palangi, Lei Zhang, Houdong Hu, Jason J. Corso, and Jianfeng Gao · 2012
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Show and tell: Lessons learned from the 2015 mscoco image captioning challenge
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan · 2016
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Uniter: Universal image-text representation learning
Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, and Jingjing Liu · 2020
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Exploring hate speech detection in multimodal publications
Raul Gomez, Jaume Gibert, Lluis Gomez, and Dimosthenis Karatzas · 2020
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Vl-bert: Pre-training of generic visual-linguistic representations
Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, and Jifeng Dai · 2020
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