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Large language models

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  1. 6 Oct
    Behavioral history improves LLM synthetic personas' individual predictions

    Researchers compared five information conditions for LLM-based synthetic personas and found that including respondents' earlier survey choices (behavioral history) substantially improves capturing between-person variation and individual informedness. Description-based personas using demographics, personality, or cognitive scores recover far less individual-level predictive accuracy than personas that include behavioral history.

    Research · 1 source

  2. 6 Oct
    Study: LLM prompting beats fine-tuned encoders for app-review emotion tags

    Researchers evaluated large language models for fine-grained, multi-label emotion classification on mobile app reviews and compared encoder fine-tuning, decoder prompting, and imbalance mitigation strategies. Decoder few-shot prompting achieved the best macro-F1 (0.642), while generative augmentation plus weighted loss improved encoders substantially with much lower inference latency.

    Research · 1 source

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