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Voices in a Crowd: Searching for clusters of unique perspectives (2024.emnlp-main)

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Challenge: Proposed solutions aim to capture minority perspectives by either modelling annotator disagreements or grouping annotators based on shared metadata.
Approach: They propose a framework that trains models without encoding annotator metadata and creates clusters of similar opinions, that are called voices.
Outcome: The proposed framework captures minority perspectives based on demographic factors in two distinct datasets while also capturing majority perspectives.

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