Papers by Shuaihan Huang
From Misleading Queries to Accurate Answers: A Three-Stage Fine-Tuning Method for LLMs (2025.findings-acl)
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| Challenge: | Existing methods focus on correcting the output but overlook the ability of LLMs to detect and correct misleading content in the input itself. |
| Approach: | They propose a three-stage fine-tuning method that improves LLMs' ability to detect and correct misleading information in input queries. |
| Outcome: | The proposed method improves accuracy and factuality of LLM responses while also reducing hallucinations. |
Reason from Future: Reverse Thought Chain Enhances LLM Reasoning (2025.findings-acl)
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Yinlong Xu, Yanzhao Zheng, Shuoshuo Sun, Shuaihan Huang, Baohua Dong, Zhu Hangcheng, Ruohui Huang, Gang Yu, Hongxia Xu, Jian Wu
| Challenge: | Existing reasoning paradigms that focus on local optimum reasoning lack global perspective. |
| Approach: | They propose a bidirectional reasoning paradigm that generates reasoning paths by bidirectional planning and bottom-up reasoning accumulation. |
| Outcome: | The proposed reasoning paradigm outperforms conventional paradigms with higher accuracy and less searching space to solve complex tasks. |