Abhijnya Bhat — accepted AI-conference papers

2026

Harnessing Diffusion-Generated Synthetic Images for Fair Image Classification

Abhipsa Basu, Aviral Gupta, Abhijnya Bhat, Venkatesh Babu Radhakrishnan

AAAI 2026technical

Image classification systems often inherit biases from uneven group representation in training data. For example, in face datasets for hair color classification, blond hair may be disproportionately associated with females, reinforcing stereotypes. A recent approach leverages the Stable Diffusion mo

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2024

Balancing Act: Distribution-Guided Debiasing in Diffusion Models

Rishubh Parihar, Abhijnya Bhat, Abhipsa Basu, Saswat Mallick, Jogendra Nath Kundu, R. Venkatesh Babu

CVPR 2024poster

Diffusion Models (DMs) have emerged as powerful generative models with unprecedented image generation capability. These models are widely used for data augmentation and creative applications. However DMs reflect the biases present in the training datasets. This is especially concerning in the contex…

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