Feb. 13, 2024, 5:49 a.m. | Prachi Jain Ashutosh Sathe Varun Gumma Kabir Ahuja Sunayana Sitaram

cs.CL updates on arXiv.org arxiv.org

Pretrained Language Models (PLMs) are widely used in NLP for various tasks. Recent studies have identified various biases that such models exhibit and have proposed methods to correct these biases. However, most of the works address a limited set of bias dimensions independently such as gender, race, or religion. Moreover, the methods typically involve finetuning the full model to maintain the performance on the downstream task. In this work, we aim to modularly debias a pretrained language model across multiple …

bias biases cs.cl cs.cy dimensions gender language language models nlp race religion set studies tasks

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