Zobrazeno 1 - 10
of 2 326
pro vyhledávání: '"Jie M"'
Publikováno v:
BMC Geriatrics, Vol 21, Iss 1, Pp 1-11 (2021)
Abstract Background Fear of falling (FoF) and physical activity (PA) are important psychological and behavioral factors associated with falls. No instrument quantifies the link between these two factors to evaluate the risk of falls. We aimed to desi
Externí odkaz:
https://doaj.org/article/68eb12c643e14f6cbb7ed69e09b68aef
Publikováno v:
Tobacco Induced Diseases, Vol 18, Iss December, Pp 1-8 (2020)
Introduction There has been considerable research on the association between smoking status and thyroid cancer risk in males, yet the findings are inconsistent. In this study, we investigated the associations of intensity, duration, cumulative dose,
Externí odkaz:
https://doaj.org/article/333bb710649c4d968c9919a9575a4726
Publikováno v:
Frontiers in Neurology, Vol 13 (2022)
IntroductionThe newly developed Composite Activity-related Risk of Falls Scale (CARFS) is designed to measure composite activity-related risk of falls (CARF) in relation to the activity-specific fear of falling and physical behavior. This study teste
Externí odkaz:
https://doaj.org/article/06d52973f211411f879834c3abfbe202
The question of how to generate high-utility mutations, to be used for testing purposes, forms a key challenge in mutation testing literature. %Existing approaches rely either on human-specified syntactic rules or learning-based approaches, all of wh
Externí odkaz:
http://arxiv.org/abs/2406.09843
Autor:
Huang, Dong, Dai, Jianbo, Weng, Han, Wu, Puzhen, Qing, Yuhao, Zhang, Jie M., Cui, Heming, Guo, Zhijiang
Large language models (LLMs) have shown remarkable progress in code generation, but their generated code often suffers from inefficiency, resulting in longer execution times and higher memory consumption. To address this issue, we propose Self Optimi
Externí odkaz:
http://arxiv.org/abs/2405.15189
Autor:
Liu, Kaibo, Liu, Yiyang, Chen, Zhenpeng, Zhang, Jie M., Han, Yudong, Ma, Yun, Li, Ge, Huang, Gang
Conventional automated test generation tools struggle to generate test oracles and tricky bug-revealing test inputs. Large Language Models (LLMs) can be prompted to produce test inputs and oracles for a program directly, but the precision of the test
Externí odkaz:
http://arxiv.org/abs/2404.10304
Autor:
Liu, Mugeng, Huang, Xiaolong, He, Wei, Xie, Yibing, Zhang, Jie M., Jing, Xiang, Chen, Zhenpeng, Ma, Yun
The Software Engineering (SE) community has been embracing the open science policy and encouraging researchers to disclose artifacts in their publications. However, the status and trends of artifact practice and quality remain unclear, lacking insigh
Externí odkaz:
http://arxiv.org/abs/2404.06852
Code generation models have increasingly become integral to aiding software development. Although current research has thoroughly examined the correctness of the code produced by code generation models, a vital aspect that plays a pivotal role in gre
Externí odkaz:
http://arxiv.org/abs/2402.02037
The advancement of natural language processing (NLP) has been significantly boosted by the development of transformer-based large language models (LLMs). These models have revolutionized NLP tasks, particularly in code generation, aiding developers i
Externí odkaz:
http://arxiv.org/abs/2312.13010
With the growing interest on Large Language Models (LLMs) for fault localization and program repair, ensuring the integrity and generalizability of the LLM-based methods becomes paramount. The code in existing widely-adopted benchmarks for these task
Externí odkaz:
http://arxiv.org/abs/2310.16253