Zobrazeno 1 - 10
of 942
pro vyhledávání: '"LI Zhitao"'
Autor:
LI Zhitao, WANG Xiaonan, LIU Xiaolin, KE Juzhong, LIU Yang, FU Chaowei, LIU Qingping, GAO Jiaojiao, SONG Jiahui, WU Kang, PENG Li, YE Xiaofang, RUAN Xiaonan
Publikováno v:
Shanghai yufang yixue, Vol 36, Iss 2, Pp 197-202 (2024)
ObjectiveTo evaluate the intervention effect of meteorological risk forecasting service on acute onset and medical expenses of chronic obstructive pulmonary disease(COPD) patients, and to provide scientific basis for the establishment of health
Externí odkaz:
https://doaj.org/article/93eefd7fd46140cba00c81f5e80dd843
Autor:
Li Lu, Li Zhitao, Cui Nannan, Huang Mingzhu, Hu Xiaoping, Hong Dongsheng, Pan Zongfu, Lu Xiaoyang
Publikováno v:
Stem Cells International, Vol 2022 (2022)
β cell dysfunction is the leading cause of diabetes. Adult β cells have matured glucose-stimulated insulin secretion (GSIS), whereas fetal and neonatal β cells are insensitive to glucose and are functionally immature. However, how β cells mature
Externí odkaz:
https://doaj.org/article/f54338edebdb42e1926947849de28d49
This paper introduces a novel privacy-preservation framework named PFID for LLMs that addresses critical privacy concerns by localizing user data through model sharding and singular value decomposition. When users are interacting with LLM systems, th
Externí odkaz:
http://arxiv.org/abs/2406.12238
Autor:
Ouyang, Sheng, Wang, Jianzong, Zhang, Yong, Li, Zhitao, Liang, Ziqi, Zhang, Xulong, Cheng, Ning, Xiao, Jing
Extractive Question Answering (EQA) in Machine Reading Comprehension (MRC) often faces the challenge of dealing with semantically identical but format-variant inputs. Our work introduces a novel approach, called the ``Query Latent Semantic Calibrator
Externí odkaz:
http://arxiv.org/abs/2404.19316
Autor:
Li, Ming, Zhang, Yong, He, Shwai, Li, Zhitao, Zhao, Hongyu, Wang, Jianzong, Cheng, Ning, Zhou, Tianyi
Instruction tuning is critical to improve LLMs but usually suffers from low-quality and redundant data. Data filtering for instruction tuning has proved important in improving both the efficiency and performance of the tuning process. But it also lea
Externí odkaz:
http://arxiv.org/abs/2402.00530
Autor:
Liao, Congyu, Cao, Xiaozhi, Iyer, Siddharth Srinivasan, Schauman, Sophie, Zhou, Zihan, Yan, Xiaoqian, Chen, Quan, Li, Zhitao, Wang, Nan, Gong, Ting, Wu, Zhe, He, Hongjian, Zhong, Jianhui, Yang, Yang, Kerr, Adam, Grill-Spector, Kalanit, Setsompop, Kawin
Publikováno v:
Magnetic Resonance in Medicine 2023
Purpose: This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and proton-density (PD), all within a clinically feasible scan time. Methods
Externí odkaz:
http://arxiv.org/abs/2312.13523
The Retrieval Question Answering (ReQA) task employs the retrieval-augmented framework, composed of a retriever and generator. The generator formulates the answer based on the documents retrieved by the retriever. Incorporating Large Language Models
Externí odkaz:
http://arxiv.org/abs/2310.18347
Recommender systems is set up to address the issue of information overload in traditional information retrieval systems, which is focused on recommending information that is of most interest to users from massive information. Generally, there is a se
Externí odkaz:
http://arxiv.org/abs/2308.15701
Autor:
Li, Ming, Zhang, Yong, Li, Zhitao, Chen, Jiuhai, Chen, Lichang, Cheng, Ning, Wang, Jianzong, Zhou, Tianyi, Xiao, Jing
In the realm of Large Language Models (LLMs), the balance between instruction data quality and quantity is a focal point. Recognizing this, we introduce a self-guided methodology for LLMs to autonomously discern and select cherry samples from open-so
Externí odkaz:
http://arxiv.org/abs/2308.12032
Autor:
Fan, Jiaxin, Zhang, Yong, Li, Hanzhang, Wang, Jianzong, Li, Zhitao, Ouyang, Sheng, Cheng, Ning, Xiao, Jing
Chinese Automatic Speech Recognition (ASR) error correction presents significant challenges due to the Chinese language's unique features, including a large character set and borderless, morpheme-based structure. Current mainstream models often strug
Externí odkaz:
http://arxiv.org/abs/2308.03423