Zobrazeno 1 - 10
of 3 273
pro vyhledávání: '"Yuntong An"'
Autor:
Zhang, Yuntong, Wang, Jiawei, Berzin, Dominic, Mirchev, Martin, Liu, Dongge, Arya, Abhishek, Chang, Oliver, Roychoudhury, Abhik
Critical open source software systems undergo significant validation in the form of lengthy fuzz campaigns. The fuzz campaigns typically conduct a biased random search over the domain of program inputs, to find inputs which crash the software system.
Externí odkaz:
http://arxiv.org/abs/2411.03346
In modern software development, multiple software components, often sourced from different contributors, including AI assistants, are combined to create a cohesive system. Although these components might each be individually safe, their composition m
Externí odkaz:
http://arxiv.org/abs/2410.18703
Autor:
Hu, Yuntong, Li, Zhuofeng, Zhang, Zheng, Ling, Chen, Kanjiani, Raasikh, Zhao, Boxin, Zhao, Liang
In this work, we present HiReview, a novel framework for hierarchical taxonomy-driven automatic literature review generation. With the exponential growth of academic documents, manual literature reviews have become increasingly labor-intensive and ti
Externí odkaz:
http://arxiv.org/abs/2410.03761
Semantic trajectories, which enrich spatial-temporal data with textual information such as trip purposes or location activities, are key for identifying outlier behaviors critical to healthcare, social security, and urban planning. Traditional outlie
Externí odkaz:
http://arxiv.org/abs/2410.00054
Autonomous program improvement typically involves automatically producing bug fixes and feature additions. Such program improvement can be accomplished by a combination of large language model (LLM) and program analysis capabilities, in the form of a
Externí odkaz:
http://arxiv.org/abs/2408.02232
Amorphization by severe plastic deformation has been observed in various crystalline materials. However, developing a quantitative and comprehensive theory for strain-induced amorphization remains challenging due to the complex nature of microstructu
Externí odkaz:
http://arxiv.org/abs/2407.19043
Polygon representation learning is essential for diverse applications, encompassing tasks such as shape coding, building pattern classification, and geographic question answering. While recent years have seen considerable advancements in this field,
Externí odkaz:
http://arxiv.org/abs/2407.00742
Autor:
Li, Zhuofeng, Gou, Zixing, Zhang, Xiangnan, Liu, Zhongyuan, Li, Sirui, Hu, Yuntong, Ling, Chen, Zhang, Zheng, Zhao, Liang
Text-Attributed Graphs (TAGs) augment graph structures with natural language descriptions, facilitating detailed depictions of data and their interconnections across various real-world settings. However, existing TAG datasets predominantly feature te
Externí odkaz:
http://arxiv.org/abs/2406.10310
Text-Attributed Graphs (TAGs) enhance graph structures with natural language descriptions, enabling detailed representation of data and their relationships across a broad spectrum of real-world scenarios. Despite the potential for deeper insights, ex
Externí odkaz:
http://arxiv.org/abs/2405.16800
Autor:
Ling, Chen, Li, Zhuofeng, Hu, Yuntong, Zhang, Zheng, Liu, Zhongyuan, Zheng, Shuang, Pei, Jian, Zhao, Liang
Textual-edge Graphs (TEGs), characterized by rich text annotations on edges, are increasingly significant in network science due to their ability to capture rich contextual information among entities. Existing works have proposed various edge-aware g
Externí odkaz:
http://arxiv.org/abs/2405.16606