1 citations · 1 across the 6 of their papers we have counts for
5 papers · 1 filter
LearNAT: Learning NL2SQL with AST-guided Task Decomposition for Large Language Models
Weibin Liao, Xin Gao, Tianyu Jia +6
Natural Language to SQL (NL2SQL) aims to translate natural language queries into executable SQL statements, offering non-expert users intuitive access to databases. While recent ap…
ProMed: Shapley Information Gain Guided Reinforcement Learning for Proactive Medical LLMs
Hongxin Ding, Baixiang Huang, Yue Fang +8
Interactive medical questioning is essential in clinical consultations, where physicians must actively gather necessary patient information. Yet existing medical Large Language Mod…
Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning
Yongxin Xu, Ruizhe Zhang, Xinke Jiang +7
Retrieval-Augmented Generation (RAG) offers an effective solution to the issues faced by Large Language Models (LLMs) in hallucination generation and knowledge obsolescence by inco…
EL4NER: Ensemble Learning for Named Entity Recognition via Multiple Small-Parameter Large Language Models
Yuzhen Xiao, Jiahe Song, Yongxin Xu +6
In-Context Learning (ICL) technique based on Large Language Models (LLMs) has gained prominence in Named Entity Recognition (NER) tasks for its lower computing resource consumption…
DRESSing Up LLM: Efficient Stylized Question-Answering via Style Subspace Editing
Xinyu Ma, Yifeng Xu, Yang Lin +5
We introduce DRESS, a novel approach for generating stylized large language model (LLM) responses through representation editing. Existing methods like prompting and fine-tuning ar…