Zobrazeno 1 - 10
of 7 361
pro vyhledávání: '"Wang, HaiBo"'
Simulating transition dynamics between metastable states is a fundamental challenge in dynamical systems and stochastic processes with wide real-world applications in understanding protein folding, chemical reactions and neural activities. However, t
Externí odkaz:
http://arxiv.org/abs/2410.15128
Publikováno v:
Journal on Internet of Things 2024, 6, 17-41
In the 6G Internet of Things (IoT) paradigm, unprecedented challenges will be raised to provide massive connectivity, ultra-low latency, and energy efficiency for ultra-dense IoT devices. To address these challenges, we explore the non-orthogonal mul
Externí odkaz:
http://arxiv.org/abs/2410.12497
Autor:
Wang, Haibo, Xu, Zhiyang, Cheng, Yu, Diao, Shizhe, Zhou, Yufan, Cao, Yixin, Wang, Qifan, Ge, Weifeng, Huang, Lifu
Video Large Language Models (Video-LLMs) have demonstrated remarkable capabilities in coarse-grained video understanding, however, they struggle with fine-grained temporal grounding. In this paper, we introduce Grounded-VideoLLM, a novel Video-LLM ad
Externí odkaz:
http://arxiv.org/abs/2410.03290
Refactoring is a critical process in software development, aiming at improving the internal structure of code while preserving its external behavior. Refactoring engines are integral components of modern Integrated Development Environments (IDEs) and
Externí odkaz:
http://arxiv.org/abs/2409.14610
Autor:
Wang, Haibo, Alidaee, Bahram
This study investigates the area of general quadratic integer programming (QIP), encompassing both unconstrained (UQIP) and constrained (CQIP) variants. These NP-hard problems have far-reaching applications, yet the non-convex cases have received lim
Externí odkaz:
http://arxiv.org/abs/2409.14176
Autor:
Niu, Zeyi, Huang, Wei, Zhang, Lei, Deng, Lin, Wang, Haibo, Yang, Yuhua, Wang, Dongliang, Li, Hong
With the rapid development of data-driven machine learning (ML) models in meteorology, typhoon track forecasts have become increasingly accurate. However, current ML models still face challenges, such as underestimating typhoon intensity and lacking
Externí odkaz:
http://arxiv.org/abs/2408.12630
Traffic forecasting uses recent measurements by sensors installed at chosen locations to forecast the future road traffic. Existing work either assumes all locations are equipped with sensors or focuses on short-term forecast. This paper studies part
Externí odkaz:
http://arxiv.org/abs/2408.02689
The recent developments of adiabatic quantum machine learning (AQML) methods and applications based on the quadratic unconstrained binary optimization (QUBO) model have received attention from academics and practitioners. Traditional machine learning
Externí odkaz:
http://arxiv.org/abs/2407.21062
Autor:
Tan, Ting Fang, Elangovan, Kabilan, Ong, Jasmine, Shah, Nigam, Sung, Joseph, Wong, Tien Yin, Xue, Lan, Liu, Nan, Wang, Haibo, Kuo, Chang Fu, Chesterman, Simon, Yeong, Zee Kin, Ting, Daniel SW
A comprehensive qualitative evaluation framework for large language models (LLM) in healthcare that expands beyond traditional accuracy and quantitative metrics needed. We propose 5 key aspects for evaluation of LLMs: Safety, Consensus, Objectivity,
Externí odkaz:
http://arxiv.org/abs/2407.07666
This study tackles the complexities of global supply chains, which are increasingly vulnerable to disruptions caused by port congestion, material shortages, and inflation. To address these challenges, we explore the application of machine learning me
Externí odkaz:
http://arxiv.org/abs/2406.13166