홈 › Papers

MIMIC: Multimodal Islamophobic Meme Identification and Classification

2024-12-01 · S M Jishanul Islam, Sahid Hossain Mustakim, Sadia Ahmmed, Md. Faiyaz Abdullah Sayeedi, Swapnil Khandoker, Syed Tasdid Azam Dhrubo, Nahid Hossain

Anti-Muslim hate speech has emerged within memes, characterized by context-dependent and rhetorical messages using text and images that seemingly mimic humor but convey Islamophobic sentiments. This work presents a novel dataset and proposes a classifier based on the Vision-and-Language Transformer (ViLT) specifically tailored to identify anti-Muslim hate within memes by integrating both visual and textual representations. Our model leverages joint modal embeddings between meme images and incorporated text to capture nuanced Islamophobic narratives that are unique to meme culture, providing both high detection accuracy and interoperability.

📄 PDF Abstract BibTeX arXiv:2412.00681

Code (1)

faiyazabdullah/MIMIC 공식 구현

Tasks

Classification

Methods 이 논문이 사용한 방법론

Attention 설명 없음

Absolute Position Encodings Absolute Position Encodings are a type of position embeddings for [Transformer-based models] where positional encodings are…

Residual Connection 설명 없음

Adam 설명 없음

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

Label Smoothing Label Smoothing is a regularization technique that introduces noise for the labels. This accounts for the fact that datasets may have mistakes in them, so maximizing the…

Dropout Dropout is a regularization technique for neural networks that drops a unit (along with connections) at training time with a specified probability $p$ (a common value is…

Dense Connections Dense Connections, or Fully Connected Connections, are a type of layer in a deep neural network that use a linear operation where every input is connected to every output…

Findings of the Shared Task on Multimodal Sentiment Analysis and Troll Meme Classification in Dravidian Languages

2022-05-01 · DravidianLangTech (ACL) 2022 5 · Premjith B, Bharathi Raja Chakravarthi, Malliga Subramanian, Bharathi B 외

This paper presents the findings of the shared task on Multimodal Sentiment Analysis and Troll meme classification in Dravidian languages held at ACL 2022. Multimodal sentiment analysis deals with the identification of s…

Classification Meme Classification Multimodal Sentiment Analysis Sentiment Analysis

SemiMemes: A Semi-supervised Learning Approach for Multimodal Memes Analysis

2023-03-31 · Pham Thai Hoang Tung, Nguyen Tan Viet, Ngo Tien Anh, Phan Duy Hung

The prevalence of memes on social media has created the need to sentiment analyze their underlying meanings for censoring harmful content. Meme censoring systems by machine learning raise the need for a semi-supervised l…

HarmTrace: Anchor-Calibrated Decoupled Optimization for Fine-Grained Target Identification in Harmful Memes

2026-08-17 · Yujia Li, Yiqun Zhang, Zihan Cheng, Yijie Huang 외 arxiv

Multimodal harmful meme detection is typically formulated as image--text harmfulness classification. A model may correctly predict harmfulness while misidentifying the attacked target or its supporting evidence. We there…

What Makes a Meme a Meme? Identifying Memes for Memetics-Aware Dataset Creation

2024-07-16 · Muzhaffar Hazman, Susan Mckeever, Josephine Griffith

Warning: This paper contains memes that may be offensive to some readers. Multimodal Internet Memes are now a ubiquitous fixture in online discourse. One strand of meme-based research is the classification of memes accor…

Meme Classification

DD-TIG at SemEval-2022 Task 5: Investigating the Relationships Between Multimodal and Unimodal Information in Misogynous Memes Detection and Classification

2022-07-01 · SemEval (NAACL) 2022 7 · Ziming Zhou, Han Zhao, Jingjing Dong, Ning Ding 외

This paper describes our submission for task 5 Multimedia Automatic Misogyny Identification (MAMI) at SemEval-2022. The task is designed to detect and classify misogynous memes. To utilize both textual and visual informa…