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Shuaihan Huang

2 accepted papers

2025

From Misleading Queries to Accurate Answers: A Three-Stage Fine-Tuning Method for LLMs

ACL 2025finding

Large language models (LLMs) exhibit excellent performance in natural language processing (NLP), but remain highly sensitive to the quality of input queries, especially when these queries contain misleading or inaccurate information. Existing methods focus on correcting the output, but they often ov…

Cited by 0SourcePDFScholar
2025

Reason from Future: Reverse Thought Chain Enhances LLM Reasoning

ACL 2025finding

It has been demonstrated that carefully designed reasoning paradigms, like Chain-of-Thought(CoT) and Tree-of-Thought(ToT), can enhance the reasoning capabilities of small language models by detailed thinking and extensive thought searching, unbounded branching factors in the searching space create p…

Cited by 0SourcePDFScholar