89 citations · 165 across the 37 of their papers we have counts for
10 papers · 1 filter
Bridging Global Intent with Local Details: A Hierarchical Representation Approach for Semantic Validation in Text-to-SQL
Rihong Qiu, Zhibang Yang, Xinke Jiang +5
Text-to-SQL translates natural language questions into SQL statements grounded in a target database schema. Ensuring the reliability and executability of such systems requires vali…
ADEPT: Continual Pretraining via Adaptive Expansion and Dynamic Decoupled Tuning
Jinyang Zhang, Yue Fang, Hongxin Ding +5
Conventional continual pretraining (CPT) for large language model (LLM) domain adaptation often suffers from catastrophic forgetting and limited domain capacity. Existing strategie…
AIMMerging: Adaptive Iterative Model Merging Using Training Trajectories for Language Model Continual Learning
Yujie Feng, Jian Li, Xiaoyu Dong +8
Continual learning (CL) is essential for deploying large language models (LLMs) in dynamic real-world environments without the need for costly retraining. Recent model merging-base…
Toward Better EHR Reasoning in LLMs: Reinforcement Learning with Expert Attention Guidance
Yue Fang, Yuxin Guo, Jiaran Gao +9
Improving large language models (LLMs) for electronic health record (EHR) reasoning is essential for enabling accurate and generalizable clinical predictions. While LLMs excel at m…
DFAMS: Dynamic-flow guided Federated Alignment based Multi-prototype Search
Zhibang Yang, Xinke Jiang, Rihong Qiu +8
Federated Retrieval (FR) routes queries across multiple external knowledge sources, to mitigate hallucinations of LLMs, when necessary external knowledge is distributed. However, e…
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…
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…
GeoEdit: Geometric Knowledge Editing for Large Language Models
Yujie Feng, Liming Zhan, Zexin Lu +6
Regular updates are essential for maintaining up-to-date knowledge in large language models (LLMs). Consequently, various model editing methods have been developed to update specif…
Recurrent Knowledge Identification and Fusion for Language Model Continual Learning
Yujie Feng, Xujia Wang, Zexin Lu +7
Continual learning (CL) is crucial for deploying large language models (LLMs) in dynamic real-world environments without costly retraining. While recent model ensemble and model me…
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…