Papers by Chuxiong Sun

1 papers
Training Language Model to Critique for Better Refinement (2025.findings-acl)

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Challenge: Large language models (LLMs) have remarkable evaluation and critique capabilities, providing insightful feedback and identifying flaws in various tasks.
Approach: They propose a framework to train critic models using refinement signals to generate feedback loops where critiques guide the model in refining its responses.
Outcome: The proposed framework outperforms traditional methods and open-source models in terms of critique quality and refinement outcomes.

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