28 citations · 40 across the 12 of their papers we have counts for
5 papers · 1 filter
Streamlining Redundant Layers to Compress Large Language Models
Xiaodong Chen, Yuxuan Hu, Jing Zhang +3
This paper introduces LLM-Streamline, a pioneer work on layer pruning for large language models (LLMs). It is based on the observation that different layers have varying impacts on…
CodeS: Towards Building Open-source Language Models for Text-to-SQL
Haoyang Li, Jing Zhang, Hanbing Liu +7
Language models have shown promising performance on the task of translating natural language questions into SQL queries (Text-to-SQL). However, most of the state-of-the-art (SOTA)…
Diversifying Question Generation over Knowledge Base via External Natural Questions
Shasha Guo, Jing Zhang, Xirui Ke +2
Previous methods on knowledge base question generation (KBQG) primarily focus on enhancing the quality of a single generated question. Recognizing the remarkable paraphrasing abili…
: Enhancing Structured Pruning via PCA Projection
Yuxuan Hu, Jing Zhang, Zhe Zhao +4
Structured pruning is a widely used technique for reducing the size of pre-trained language models (PLMs), but current methods often overlook the potential of compressing the hidde…
JarKA: Modeling Attribute Interactions for Cross-lingual Knowledge Alignment
Bo Chen, Jing Zhang, Xiaobin Tang +2
Abstract. Cross-lingual knowledge alignment is the cornerstone in building a comprehensive knowledge graph (KG), which can benefit various knowledge-driven applications. As the str…