Zobrazeno 1 - 10
of 19 779
pro vyhledávání: '"An, Xuejiao"'
In the context of Industry 4.0, the manufacturing sector is increasingly facing the challenge of data usability, which is becoming a widespread phenomenon and a new contemporary concern. In response, Data Governance (DG) emerges as a viable avenue to
Externí odkaz:
http://arxiv.org/abs/2409.15137
Omnidirectional depth estimation has received much attention from researchers in recent years. However, challenges arise due to camera soiling and variations in camera layouts, affecting the robustness and flexibility of the algorithm. In this paper,
Externí odkaz:
http://arxiv.org/abs/2409.14766
Autor:
Li, Ming, Yang, Xiong, Wu, Chaofan, Li, Jiaheng, Wang, Pinzhi, Hu, Xuejiao, Du, Sidan, Li, Yang
Omnidirectional Depth Estimation has broad application prospects in fields such as robotic navigation and autonomous driving. In this paper, we propose a robotic prototype system and corresponding algorithm designed to validate omnidirectional depth
Externí odkaz:
http://arxiv.org/abs/2409.07843
Freeform thin-shell surfaces are critical in various fields, but their fabrication is complex and costly. Traditional methods are wasteful and require custom molds, while 3D printing needs extensive support structures and post-processing. Thermoshrin
Externí odkaz:
http://arxiv.org/abs/2407.19533
Autor:
Zhang, Wenjing, Xiao, Siqi, Lei, Xuejiao, Wang, Ning, Zhang, Huazheng, An, Meijuan, Yang, Bikun, Liu, Zhaoxiang, Wang, Kai, Lian, Shiguo
The rapid growth of large language models(LLMs) has emerged as a prominent trend in the field of artificial intelligence. However, current state-of-the-art LLMs are predominantly based on English. They encounter limitations when directly applied to t
Externí odkaz:
http://arxiv.org/abs/2406.18192
In the era of Industry 4.0, artificial intelligence (AI) is assuming an increasingly pivotal role within industrial systems. Despite the recent trend within various industries to adopt AI, the actual adoption of AI is not as developed as perceived. A
Externí odkaz:
http://arxiv.org/abs/2406.15784
In the dynamic landscape of contemporary business, the wave in data and technological advancements has directed companies toward embracing data-driven decision-making processes. Despite the vast potential that data holds for strategic insights and op
Externí odkaz:
http://arxiv.org/abs/2407.06199
Autor:
Zhang, Wenjing, Lei, Xuejiao, Liu, Zhaoxiang, An, Meijuan, Yang, Bikun, Zhao, KaiKai, Wang, Kai, Lian, Shiguo
With the profound development of large language models(LLMs), their safety concerns have garnered increasing attention. However, there is a scarcity of Chinese safety benchmarks for LLMs, and the existing safety taxonomies are inadequate, lacking com
Externí odkaz:
http://arxiv.org/abs/2406.10311
Autor:
Lian, Shiguo, Zhao, Kaikai, Liu, Xinhui, Lei, Xuejiao, Yang, Bikun, Zhang, Wenjing, Wang, Kai, Liu, Zhaoxiang
General large language models enhanced with supervised fine-tuning and reinforcement learning from human feedback are increasingly popular in academia and industry as they generalize foundation models to various practical tasks in a prompt manner. To
Externí odkaz:
http://arxiv.org/abs/2406.10307
Autor:
Wei, Jianyong, Liu, Yumeng, Wang, Yizhuo, Li, Kai, Lian, Zhentao, Xie, Maosong, Yang, Xinhan, Khaleghi, Seyed Saleh Mousavi, Dai, Fuxing, Hu, Weida, Gao, Xuejiao, Yang, Rui, Dan, Yaping
High-gain photodetectors based on two-dimensional (2D) semiconductors, in particular those in photoconductive mode, have been extensively investigated in the past decade. However, the classical photoconductive theory was derived on two misplaced assu
Externí odkaz:
http://arxiv.org/abs/2405.16209