4 papers
LexSemBridge: Fine-Grained Dense Representation Enhancement through Token-Aware Embedding Augmentation
Shaoxiong Zhan, Hai Lin, Hongming Tan +6
As queries in retrieval-augmented generation (RAG) pipelines powered by large language models (LLMs) become increasingly complex and diverse, dense retrieval models have demonstrat…
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…
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…
Loss-Aware Curriculum Learning for Chinese Grammatical Error Correction
Ding Zhang, Yangning Li, Lichen Bai +6
Chinese grammatical error correction (CGEC) aims to detect and correct errors in the input Chinese sentences. Recently, Pre-trained Language Models (PLMS) have been employed to imp…