Papers by Weiguo Fan

1 papers
Instances Need More Care: Rewriting Prompts for Instances with LLMs in the Loop Yields Better Zero-Shot Performance (2024.findings-acl)

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Challenge: Large language models (LLMs) have revolutionized zero-shot task performance, mitigating the need for task-specific annotations while enhancing task generalizability.
Approach: They propose an approach that optimizes the zero-shot prompts for individual task instances following an innovative manner of "LLMs in the loop" their results show that PRomPTed outperforms naive zero- shot approaches and a strong baseline which refines the task output instead of the input prompt.
Outcome: The proposed approach outperforms naive approaches and a strong baseline which refines the task output instead of the input prompt.

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