7 papers · 1 filter
INSPIRE: An Internalize-Then-Improve Approach for Example-Driven Mathematical Reasoning
Shuai Wang, Jiayi Kuang, Yinghui Li +4
Mathematical reasoning has seen rapid progress in large language models (LLMs), yet existing methods optimize predominantly for final-answer correctness, raising the question wheth…
Atomic Thinking of LLMs: Decoupling and Exploring Mathematical Reasoning Abilities
Jiayi Kuang, Haojing Huang, Yinghui Li +8
Large Language Models (LLMs) have demonstrated outstanding performance in mathematical reasoning capabilities. However, we argue that current large-scale reasoning models primarily…
Refine Knowledge of Large Language Models via Adaptive Contrastive Learning
Yinghui Li, Haojing Huang, Jiayi Kuang +7
How to alleviate the hallucinations of Large Language Models (LLMs) has always been the fundamental goal pursued by the LLMs research community. Looking through numerous hallucinat…
CLEME2.0: Towards Interpretable Evaluation by Disentangling Edits for Grammatical Error Correction
Jingheng Ye, Zishan Xu, Yinghui Li +9
The paper focuses on the interpretability of Grammatical Error Correction (GEC) evaluation metrics, which received little attention in previous studies. To bridge the gap, we intro…
EXCGEC: A Benchmark for Edit-Wise Explainable Chinese Grammatical Error Correction
Jingheng Ye, Shang Qin, Yinghui Li +8
Existing studies explore the explainability of Grammatical Error Correction (GEC) in a limited scenario, where they ignore the interaction between corrections and explanations and…
Mitigating Catastrophic Forgetting in Multi-domain Chinese Spelling Correction by Multi-stage Knowledge Transfer Framework
Peng Xing, Yinghui Li, Shirong Ma +6
Chinese Spelling Correction (CSC) aims to detect and correct spelling errors in given sentences. Recently, multi-domain CSC has gradually attracted the attention of researchers bec…