Papers with social science task downstream

    1 papers
    Just Put a Human in the Loop? Investigating LLM-Assisted Annotation for Subjective Tasks (2025.findings-acl)

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    Challenge: Large language models (LLMs) have shown impressive performance in many annotation tasks, including subjective tasks common in content moderation and text analysis in the social sciences.
    Approach: They propose to give crowdworkers LLM-generated annotation suggestions to "review" LLMs for subjective tasks can impact model performance and analysis downstream .
    Outcome: The proposed approach improves self-reported confidence in annotators and models . it also significantly improves model performance by analyzing human-approved datasets.

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