Papers by Cui Danxin

1 papers
Data-Efficient Selection via Grammatical Complexity in Continual Pre-training of Domain-Specific LLMs (2025.emnlp-main)

Copied to clipboard

Challenge: Existing data selection strategies for continual pre-training of large language models often rely on scarce labeled data or computationally expensive LLMs.
Approach: They propose an annotation-independent data selection framework for CPT that evaluates grammatical complexity using lexical diversity and syntactic complexity.
Outcome: The proposed framework outperforms baselines on a financial dataset and surpasses full-data training by 1.7% using only 20% of the data.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations