Multimodal zero-shot hateful meme detection
Facebook has recently launched the hateful meme detection challenge, which garnered much attention in academic and industry research communities. Researchers have proposed multimodal deep learning classification methods to perform hateful meme detection. While the proposed methods have yielded promi...
Saved in:
Main Authors: | ZHU, Jiawen, LEE, Roy Ka-Wei, CHONG, Wen Haw |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2022
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/8257 https://ink.library.smu.edu.sg/context/sis_research/article/9260/viewcontent/Multimodal_Zero_Shot_Hateful_Meme_Detection.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Disentangling hate in online memes
by: LEE, Ka Wei, Roy, et al.
Published: (2021) -
On explaining multimodal hateful meme detection models
by: HEE, Ming Shan, et al.
Published: (2022) -
Prompting for multimodal hateful meme classification
by: CAO, Rui, et al.
Published: (2022) -
Pro-Cap: Leveraging a frozen vision-language model for hateful meme detection
by: CAO, Rui, et al.
Published: (2023) -
MERMAID: A dataset and framework for multimodal meme semantic understanding
by: TOH, Shaun, et al.
Published: (2023)