Papers Hateful Meme Classification
“Hateful Meme Classification” 태그가 달린 논문 17편 · 필터 해제
LLM-based Semantic Augmentation for Harmful Content Detection
Recent advances in large language models (LLMs) have demonstrated strong performance on simple text classification tasks, frequently under zero-shot settings. However, their efficacy declines when tackling complex social…
ClassificationHateful Meme ClassificationMeme ClassificationPropaganda detection+2Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme Detection
Hateful memes have become a significant concern on the Internet, necessitating robust automated detection systems. While LMMs have shown promise in hateful meme detection, they face notable challenges like sub-optimal pe…
Contrastive LearningDomain GeneralizationHateful Meme ClassificationIn-Context Learning+2Demystifying Hateful Content: Leveraging Large Multimodal Models for Hateful Meme Detection with Explainable Decisions
Hateful meme detection presents a significant challenge as a multimodal task due to the complexity of interpreting implicit hate messages and contextual cues within memes. Previous approaches have fine-tuned pre-trained …
Hateful Meme ClassificationMeme ClassificationPrompt-enhanced Network for Hateful Meme Classification
The dynamic expansion of social media has led to an inundation of hateful memes on media platforms, accentuating the growing need for efficient identification and removal. Acknowledging the constraints of conventional mu…
ClassificationContrastive LearningHateful Meme ClassificationLanguage Modelling+2MemeCLIP: Leveraging CLIP Representations for Multimodal Meme Classification
The complexity of text-embedded images presents a formidable challenge in machine learning given the need for multimodal understanding of multiple aspects of expression conveyed by them. While previous research in multim…
ClassificationHateful Meme ClassificationHumor DetectionMeme ClassificationTowards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models
The age of social media is flooded with Internet memes, necessitating a clear grasp and effective identification of harmful ones. This task presents a significant challenge due to the implicit meaning embedded in memes, …
Hateful Meme ClassificationLanguage ModellingSmall Language ModelText GenerationImproving Hateful Meme Detection through Retrieval-Guided Contrastive Learning
Hateful memes have emerged as a significant concern on the Internet. Detecting hateful memes requires the system to jointly understand the visual and textual modalities. Our investigation reveals that the embedding space…
Contrastive LearningHateful Meme ClassificationMeme ClassificationRetrievalMapping Memes to Words for Multimodal Hateful Meme Classification
Multimodal image-text memes are prevalent on the internet, serving as a unique form of communication that combines visual and textual elements to convey humor, ideas, or emotions. However, some memes take a malicious tur…
Hateful Meme ClassificationLanguage ModelingLanguage ModellingMeme ClassificationDecoding the Underlying Meaning of Multimodal Hateful Memes
Recent studies have proposed models that yielded promising performance for the hateful meme classification task. Nevertheless, these proposed models do not generate interpretable explanations that uncover the underlying …
BenchmarkingHateful Meme ClassificationMeme ClassificationPrompting for Multimodal Hateful Meme Classification
Hateful meme classification is a challenging multimodal task that requires complex reasoning and contextual background knowledge. Ideally, we could leverage an explicit external knowledge base to supplement contextual an…
ClassificationHateful Meme ClassificationLanguage ModelingLanguage Modelling+1Hate-CLIPper: Multimodal Hateful Meme Classification based on Cross-modal Interaction of CLIP Features
Hateful memes are a growing menace on social media. While the image and its corresponding text in a meme are related, they do not necessarily convey the same meaning when viewed individually. Hence, detecting hateful mem…
Hateful Meme ClassificationMeme Classification0/1 Deep Neural Networks via Block Coordinate Descent
The step function is one of the simplest and most natural activation functions for deep neural networks (DNNs). As it counts 1 for positive variables and 0 for others, its intrinsic characteristics (e.g., discontinuity a…
10-shot image generation16k2D Object Detection+92On Explaining Multimodal Hateful Meme Detection Models
Hateful meme detection is a new multimodal task that has gained significant traction in academic and industry research communities. Recently, researchers have applied pre-trained visual-linguistic models to perform the m…
ClassificationHateful Meme ClassificationMeme ClassificationDetecting Harmful Memes and Their Targets
Among the various modes of communication in social media, the use of Internet memes has emerged as a powerful means to convey political, psychological, and socio-cultural opinions. Although memes are typically humorous i…
Hateful Meme ClassificationDisentangling Hate in Online Memes
Hateful and offensive content detection has been extensively explored in a single modality such as text. However, such toxic information could also be communicated via multimodal content such as online memes. Therefore, …
ClassificationHateful Meme ClassificationMeme ClassificationVL-BERT+: Detecting Protected Groups in Hateful Multimodal Memes
This paper describes our submission (winning solution for Task A) to the Shared Task on Hateful Meme Detection at WOAH 2021. We build our system on top of a state-of-the-art system for binary hateful meme classification …
Data AugmentationHateful Meme ClassificationMeme ClassificationLearning Transferable Visual Models From Natural Language Supervision
State-of-the-art computer vision systems are trained to predict a fixed set of predetermined object categories. This restricted form of supervision limits their generality and usability since additional labeled data is n…
Action RecognitionBenchmarkingFew-Shot Image Classificationgeo-localization+21