Papers by Hanqing Gao

2 papers
ARM: An Alignment-and-Replacement Module for Chinese Spelling Check Based on LLMs (2024.emnlp-main)

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Challenge: Chinese Spelling Check (CSC) aims to identify and correct spelling errors in Chinese texts, where enhanced semantic understanding of a sentence can significantly improve correction accuracy.
Approach: They propose a plug-and-play Alignment-and -Replacement module that enhances existing Chinese CSC models without retraining or fine-tuning.
Outcome: The proposed module improves existing models while reducing retraining and fine-tuning.
InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes Under Herd Behavior (2025.acl-long)

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Challenge: relying on authentic data for Supervised Fine-Tuning (SFT) is costly and expensive.
Approach: They propose a framework that constructs high-quality SFT datasets by leveraging theoretical solutions to similar and simple optimal investment problems rather than the complex scenarios.
Outcome: The proposed framework achieves faster parameter convergence than using real-user data, suggesting superior learning efficiency.

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