Papers by Aditya Chinchure

2 papers
From Local Concepts to Universals: Evaluating the Multicultural Understanding of Vision-Language Models (2024.emnlp-main)

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Challenge: Vision-Language Models (VLMs) have shown emerging capabilities through large-scale training that have made them gain popularity in recent years.
Approach: They propose to perform retrieval across universals and cultural visual grounding tasks to assess cultural diversity across universal and culture-specific local concepts.
Outcome: The proposed benchmarks show that the models perform significantly across cultures, underscoring the need for enhancing multicultural understanding in vision-language models.
Mitigate One, Skew Another? Tackling Intersectional Biases in Text-to-Image Models (2025.findings-emnlp)

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Challenge: a new tool for analyzing and quantifying bias interactions in text-to-image models is being developed . a bias in text models can be deeply interrelated, but measuring such effects quantitatively remains a challenge.
Approach: They propose a tool to quantify bias interactions in text-to-image models by analyzing and quantifying bias interactions along bias axes.
Outcome: a new tool analyzes and quantifies bias interactions in text-to-image models . estimates show strong correlations with observed post-mitigation outcomes .

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