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Sangmitra Madhusudan

2 accepted papers

2025

Fine-Tuned LLMs are “Time Capsules” for Tracking Societal Bias Through Books

NAACL 2025long

Books, while often rich in cultural insights, can also mirror societal biases of their eras—biases that Large Language Models (LLMs) may learn and perpetuate during training. We introduce a novel method to trace and quantify these biases using fine-tuned LLMs. We develop BookPAGE, a corpus comprisin…

2024

STOP! Benchmarking Large Language Models with Sensitivity Testing on Offensive Progressions

EMNLP 2024main

Mitigating explicit and implicit biases in Large Language Models (LLMs) has become a critical focus in the field of natural language processing. However, many current methodologies evaluate scenarios in isolation, without considering the broader context or the spectrum of potential biases within eac…