Papers by Yingming Wang

1 papers
Self-Critique and Refinement for Faithful Natural Language Explanations (2025.emnlp-main)

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Challenge: Existing work has demonstrated that Large Language Models (LLMs) can self-critique and refine their initial outputs, but this capability remains unexplored for improving explanation faithfulness.
Approach: They propose a framework that enables models to improve the faithfulness of their own explanations through an iterative critique and refinement process without external supervision.
Outcome: The proposed framework reduces unfaithfulness rates in three datasets and four state-of-the-art LLMs by 36% compared to 54.81% for baseline.

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