In this context, the hateful meme detection task is extremely challenging, especially due to memes' multimodal nature, i.e., they have two different sources: image and text. Consequently, when dealing with memes, a classification model needs to tackle both components in order to classify them as hateful or not-hateful.
Mar 24, 2023
Mar 24, 2023 · Methods that detect hate speech in memes have become vital in our connected society, especially in the context of many social media ...
Detecting hate speech in memes requires reasoning about subtle cues and the task was constructed such that unimodal models find it difficult, by including “ ...
Feb 18, 2024 · Detecting hate speech in memes: a review. Artificial Intelligence ... Multimodal hate speech detection from ben- gali memes and texts.
Nov 12, 2023 · Despite that, there is a lack of related work on detecting or correcting hateful memes with VLMs. In this work, we study the ability of VLMs on ...
Summary and Contributions: The paper proposes a challenge in detecting hate speech in multimodal memes (text + image; the problem is posed as binary ...
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Mar 24, 2023 · Methods that detect hate speech in memes have become vital in our connected society, especially in the context of many social media ...
May 9, 2024 · This project aims to explore and develop effective techniques for detecting hate speech within multimodal memes, aiming to construct a robust ...
This paper focuses on hate speech detection in multi-modal memes wherein memes pose an interesting multi- modal fusion problem and tackles the benign text ...
The project work proposes to solve the problem of automatically classifying memes as to being hateful or not by combining text, image feature information and ...