5 papers
RAISE: Reinforced Adaptive Instruction Selection For Large Language Models
Qingsong Lv, Yangning Li, Zihua Lan +8
In the instruction fine-tuning of large language models (LLMs), it is widely recognized that a few high-quality instructions are superior to a large number of low-quality instructi…
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…
Revisiting Classification Taxonomy for Grammatical Errors
Deqing Zou, Jingheng Ye, Yulu Liu +7
Grammatical error classification plays a crucial role in language learning systems, but existing classification taxonomies often lack rigorous validation, leading to inconsistencie…
DAST: Context-Aware Compression in LLMs via Dynamic Allocation of Soft Tokens
Shaoshen Chen, Yangning Li, Zishan Xu +4
Large Language Models (LLMs) face computational inefficiencies and redundant processing when handling long context inputs, prompting a focus on compression techniques. While existi…
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…