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Ilyas Khan

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Vision-Language Models Exhibit Geographical Bias in Indian Face Recognition

Vision-Language Models (VLMs) demonstrate significant geographical bias within their representations of Indian demographics, stemming from the oversimplification of India's diverse population in existing fairness datasets. The IndicFairFace dataset, a novel and balanced compilation of 14,400 images, was developed to address this limitation by uniformly representing India's diverse states and genders. This dataset enables quantification and mitigation of intra-national geographical bias in VLMs with minimal impact on model performance.

Pictorial Mathematics Lowers Barrier to Quantum Education

Quantum Picturalism, a novel visual mathematical language, has demonstrated significant potential as an educational methodology. A pilot study showed high school students, without advanced mathematical prerequisites, achieved an 82% pass rate on university-level quantum exams. This approach could broaden participation in quantum computing by lowering traditional cognitive and demographic barriers.