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References (32)

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FairImagen: Post-Processing for Bias Mitigation in Text-to-Image Models
2025Zihao Fu, Ryan Brown et al.
[2]
Dissecting and Mitigating Diffusion Bias via Mechanistic Interpretability
2025Yingdong Shi, Changming Li et al.
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FairT2I: Mitigating Social Bias in Text-to-Image Generation via Large Language Model-Assisted Detection and Attribute Rebalancing
2025Jinya Sakurai, Issei Sato
[4]
Gender Bias in Text-to-Video Generation Models: A Case Study of Sora
2024Mohammad Nadeem, S. Sohail et al.
[5]
Open-Sora: Democratizing Efficient Video Production for All
2024Zangwei Zheng, Xiangyu Peng et al.
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2024Yilei Jiang, Weihong Li et al.
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2024Jaehong Yoon, Shoubin Yu et al.
[8]
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2024Kimia Hamidieh, Haoran Zhang et al.
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2024Eunji Kim, Siwon Kim et al.
[10]
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2024Zhuoyi Yang, Jiayan Teng et al.
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2024Md Mehrab Tanjim, K. Singh et al.
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2023Hang Li, Chengzhi Shen et al.
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2023Cheng Zhang, Xuanbai Chen et al.
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2023Yushi Hu, Benlin Liu et al.
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Founder's Pitch

"FairT2V offers a training-free solution to mitigate gender bias in text-to-video diffusion models, enhancing fairness without compromising video quality."

Generative VideoScore: 6View PDF ↗

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0-10 scale

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1/4 signals

2.5

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2/4 signals

5

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3/4 signals

7.5

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