Papers by Narjis Asad

2 papers
“You are Beautiful, Body Image Stereotypes are Ugly!” BIStereo: A Benchmark to Measure Body Image Stereotypes in Language Models (2025.findings-acl)

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Challenge: BIStereo is a suite of language models that uncover body image stereotypes in language models.
Approach: They propose a metric, TriSentBias, that captures the biased preferences of LMs towards a certain body type over others.
Outcome: The proposed metric captures biased preferences of LMs towards a certain body type over others.
IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Context (2024.naacl-long)

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Challenge: Existing benchmark datasets focus on English language and the Western context, leaving a void for a reliable dataset that encapsulates India’s unique socio-cultural nuances.
Approach: They propose to use CrowS-Pairs to create a benchmark dataset that captures and evaluates social biases in Large Language Models (LLMs).
Outcome: The proposed dataset is available in English and Hindi and leverages LLMs ChatGPT and InstructGPT to augment the existing dataset with diverse societal biases and stereotypes prevalent in India.

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