Papers by Chaoyi Ruan

1 papers
PMPO: Probabilistic Metric Prompt Optimization for Small and Large Language Models (2025.findings-emnlp)

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Challenge: Existing methods evaluate candidate prompts by sampling full outputs, often coupled with self critique or human annotated preferences, which limits scalability, especially for smaller models or models that are not instruction tuned.
Approach: They propose a framework that uses token level cross entropy as a direct, lightweight evaluation signal to evaluate candidate prompts.
Outcome: The proposed framework outperforms prior prompt optimizers across model sizes and datasets.

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