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Michelle YoungJin Kim

2 accepted papers

2024

ABLE: Agency-BeLiefs Embedding to Address Stereotypical Bias through Awareness Instead of Obliviousness

COLING 2024main

Natural Language Processing (NLP) models tend to inherit and amplify stereotypical biases present in their training data, leading to harmful societal consequences. Current efforts to rectify these biases typically revolve around making models oblivious to bias, which is at odds with the idea that hu…

2022

CLoSE: Contrastive Learning of Subframe Embeddings for Political Bias Classification of News Media

COLING 2022main

Framing is a political strategy in which journalists and politicians emphasize certain aspects of a societal issue in order to influence and sway public opinion. Frameworks for detecting framing in news articles or social media posts are critical in understanding the spread of biased information in…