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20232026
most citedSituating the social issues of image generation models in the model life cycle: a sociotechnical approach

14 citations · 16 across the 11 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

No Annotations for Object Detection in Art through Stable Diffusion

Patrick Ramos, Nicolas Gonthier, Selina Khan +2

Object detection in art is a valuable tool for the digital humanities, as it allows for faster identification of objects in artistic and historical images compared to humans. Howev…

cs.CY2024★ 1 cited

Gender Bias Evaluation in Text-to-image Generation: A Survey

Yankun Wu, Yuta Nakashima, Noa Garcia

The rapid development of text-to-image generation has brought rising ethical considerations, especially regarding gender bias. Given a text prompt as input, text-to-image models ge…

cs.MM2024

Enhancing Fake News Detection in Social Media via Label Propagation on Cross-modal Tweet Graph

Wanqing Zhao, Yuta Nakashima, Haiyuan Chen +1

Fake news detection in social media has become increasingly important due to the rapid proliferation of personal media channels and the consequential dissemination of misleading in…

cs.CV2024

Would Deep Generative Models Amplify Bias in Future Models?

Tianwei Chen, Yusuke Hirota, Mayu Otani +2

We investigate the impact of deep generative models on potential social biases in upcoming computer vision models. As the internet witnesses an increasing influx of AI-generated im…

cs.CV2024

Towards Artwork Explanation in Large-scale Vision Language Models

Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2

Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…