HateProof: Are Hateful Meme Detection Systems really Robust?-Reference-Cited by-同舟云学术

HateProof: Are Hateful Meme Detection Systems really Robust?

Published:2023-04-30 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2023
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Author:

Aggarwal Piush¹^ORCID,Chawla Pranit²^ORCID,Das Mithun²^ORCID,Saha Punyajoy²^ORCID,Mathew Binny²^ORCID,Zesch Torsten¹^ORCID,Mukherjee Animesh²^ORCID

Affiliation:

1. FernUniversität in Hagen, Germany

2. Indian Institute of Technology Kharagpur, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3543507.3583356

Reference88 articles.

1. Tariq Habib Afridi Aftab Alam Muhammad Numan Khan Jawad Khan and Young-Koo Lee. 2020. A Multimodal Memes Classification: A Survey and Open Research Issues. https://doi.org/10.48550/ARXIV.2009.08395 10.48550/ARXIV.2009.08395

2. Tariq Habib Afridi Aftab Alam Muhammad Numan Khan Jawad Khan and Young-Koo Lee. 2020. A Multimodal Memes Classification: A Survey and Open Research Issues. https://doi.org/10.48550/ARXIV.2009.08395

3. VL-BERT+: Detecting Protected Groups in Hateful Multimodal Memes

4. Natalie Alkiviadou . 2019. Hate speech on social media networks: towards a regulatory framework?Information & Communications Technology Law 28, 1 ( 2019 ), 19–35. https://doi.org/10.1080/13600834.2018.1494417 arXiv:https://doi.org/10.1080/13600834.2018.1494417 10.1080/13600834.2018.1494417 Natalie Alkiviadou. 2019. Hate speech on social media networks: towards a regulatory framework?Information & Communications Technology Law 28, 1 (2019), 19–35. https://doi.org/10.1080/13600834.2018.1494417 arXiv:https://doi.org/10.1080/13600834.2018.1494417

5. Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering

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