2025
ACL
ACL 2025
AI Tools Can Generate Misculture Visuals! Detecting Prompts Generating Misculture Visuals For Prevention
Abstract
AbstractAdvanced AI models that generate realistic images from text prompts offer new creative possibilities but also risk producing culturally insensitive or offensive content. To address this issue, we introduce a novel dataset designed to classify text prompts that could lead to the generation of harmful images misrepresenting different cultures and communities. By training machine learning models on this dataset, we aim to automatically identify and filter out harmful prompts before image generation, balancing cultural sensitivity with creative freedom. Benchmarking with state-ofthe-art language models, our baseline models achieved an accuracy of 73.34%.
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Interdisciplinary Bridge
— Artificial Intelligence and Computer Vision and Deep Learning and Machine Learning
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Artificial Intelligence > Core AI > Responsible AI
Machine Learning > Core Methods > Classification
Deep Learning > Techniques > Pretraining
Computer Vision > Generation > Image Generation
Artificial Intelligence > Core AI > Fairness
Machine Learning > Learning Types > Classification
Deep Learning > Learning Types > Classification