5 papers
Variational autoencoder for inference of nonlinear mixed effect models based on ordinary differential equations
Zhe Li, Mélanie Prague, Rodolphe Thiébaut +1
We propose a variational autoencoder (VAE) approach for parameter estimation in nonlinear mixed-effects models based on ordinary differential equations (NLME-ODEs) using longitudin…
KRAL: Knowledge and Reasoning Augmented Learning for LLM-assisted Clinical Antimicrobial Therapy
Zhe Li, Yehan Qiu, Yujie Chen +1
Clinical antimicrobial therapy requires the dynamic integration of pathogen profiles,host factors, pharmacological properties of antimicrobials,and the severity of infection. This…
BLM: A Boundless Large Model for Cross-Space, Cross-Task, and Cross-Embodiment Learning
Wentao Tan, Bowen Wang, Heng Zhi +15
Multimodal large language models (MLLMs) have advanced vision-language reasoning and are increasingly deployed in embodied agents. However, significant limitations remain: MLLMs ge…
DL-QAT: Weight-Decomposed Low-Rank Quantization-Aware Training for Large Language Models
Wenjin Ke, Zhe Li, Dong Li +2
Improving the efficiency of inference in Large Language Models (LLMs) is a critical area of research. Post-training Quantization (PTQ) is a popular technique, but it often faces ch…
Bridging the User-side Knowledge Gap in Knowledge-aware Recommendations with Large Language Models
Zheng Hu, Zhe Li, Ziyun Jiao +5
In recent years, knowledge graphs have been integrated into recommender systems as item-side auxiliary information, enhancing recommendation accuracy. However, constructing and int…