Zobrazeno 1 - 10
of 56 890
pro vyhledávání: '"Yuan-Yuan An"'
Autor:
Jiang, Haiyang, Chen, Tong, Zhang, Wentao, Hung, Nguyen Quoc Viet, Yuan, Yuan, Li, Yong, Cui, Lizhen
Urban flow prediction is a classic spatial-temporal forecasting task that estimates the amount of future traffic flow for a given location. Though models represented by Spatial-Temporal Graph Neural Networks (STGNNs) have established themselves as ca
Externí odkaz:
http://arxiv.org/abs/2412.05534
With global urbanization, the focus on sustainable cities has largely grown, driving research into equity, resilience, and urban planning, which often relies on mobility data. The rise of web-based apps and mobile devices has provided valuable user d
Externí odkaz:
http://arxiv.org/abs/2412.05000
Autor:
Ding, Jingtao, Zhang, Yunke, Shang, Yu, Zhang, Yuheng, Zong, Zefang, Feng, Jie, Yuan, Yuan, Su, Hongyuan, Li, Nian, Sukiennik, Nicholas, Xu, Fengli, Li, Yong
The concept of world models has garnered significant attention due to advancements in multimodal large language models such as GPT-4 and video generation models such as Sora, which are central to the pursuit of artificial general intelligence. This s
Externí odkaz:
http://arxiv.org/abs/2411.14499
Urban spatio-temporal flow prediction, encompassing traffic flows and crowd flows, is crucial for optimizing city infrastructure and managing traffic and emergency responses. Traditional approaches have relied on separate models tailored to either gr
Externí odkaz:
http://arxiv.org/abs/2411.12972
The urban environment is characterized by complex spatio-temporal dynamics arising from diverse human activities and interactions. Effectively modeling these dynamics is essential for understanding and optimizing urban systems In this work, we introd
Externí odkaz:
http://arxiv.org/abs/2411.12164
Texts on the intelligent transportation scene include mass information. Fully harnessing this information is one of the critical drivers for advancing intelligent transportation. Unlike the general scene, detecting text in transportation has extra de
Externí odkaz:
http://arxiv.org/abs/2411.02794
Automated unit test generation has been widely studied, with Large Language Models (LLMs) recently showing significant potential. Moreover, in the context of unit test generation, these tools prioritize high code coverage, often at the expense of pra
Externí odkaz:
http://arxiv.org/abs/2410.13542
Autor:
Li, Yan, Li, Mingyi, Zhang, Xiao, Xu, Guangwei, Chen, Feng, Yuan, Yuan, Zou, Yifei, Zhao, Mengying, Lu, Jianbo, Yu, Dongxiao
In this work, we study to release the potential of massive heterogeneous weak computing power to collaboratively train large-scale models on dispersed datasets. In order to improve both efficiency and accuracy in resource-adaptive collaborative learn
Externí odkaz:
http://arxiv.org/abs/2410.08457
In real world software development, improper or missing exception handling can severely impact the robustness and reliability of code. Exception handling mechanisms require developers to detect, capture, and manage exceptions according to high standa
Externí odkaz:
http://arxiv.org/abs/2410.06949
Large Vision-Language Models (LVLMs) have achieved remarkable progress on visual perception and linguistic interpretation. Despite their impressive capabilities across various tasks, LVLMs still suffer from the issue of hallucination, which involves
Externí odkaz:
http://arxiv.org/abs/2410.04107