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cs.CV2026
Newer Is Not Fairer: Gender Stereotyping in Text-to-Image AI Across Model Generations
Shesh Narayan Gupta, Nik Bear Brown
Text-to-image generative models are widely used in professional and creative settings, yet how they represent gender across occupations -- and whether newer models are fairer -- re…
cs.CV2026
When Generative Augmentation Hurts: A Benchmark Study of GAN and Diffusion Models for Bias Correction in AI Classification Systems
Shesh Narayan Gupta, Nik Bear Brown
Generative models are widely used to compensate for class imbalance in AI training pipelines, yet their failure modes under low-data conditions are poorly understood. This paper re…