Papers by Sarumi Oluyemi

    1 papers
    Corpus Considerations for Annotator Modeling and Scaling (2024.naacl-long)

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    Challenge: Recent trends in natural language processing and annotation tasks emphasize individual perspectives . annotator models that rely on a single ground truth may disregard valuable minority perspectives omissions .
    Approach: They propose a composite embedding approach to investigate annotator modeling techniques . they show that the commonly used user token model consistently outperforms more complex models .
    Outcome: The proposed model outperforms more complex models on a given dataset.

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