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pro vyhledávání: '"Tian Bowen"'
Recent studies have highlighted the significant potential of Large Language Models (LLMs) as zero-shot relevance rankers. These methods predominantly utilize prompt learning to assess the relevance between queries and documents by generating a ranked
Externí odkaz:
http://arxiv.org/abs/2411.04539
In the rapidly evolving field of deep learning, specialized models have driven significant advancements in tasks such as computer vision and natural language processing. However, this specialization leads to a fragmented ecosystem where models lack t
Externí odkaz:
http://arxiv.org/abs/2410.05746
Fine-grained image classification has witnessed significant advancements with the advent of deep learning and computer vision technologies. However, the scarcity of detailed annotations remains a major challenge, especially in scenarios where obtaini
Externí odkaz:
http://arxiv.org/abs/2409.03192
Autor:
Wang, Yihang, Huang, Xu, Tian, Bowen, Su, Yueyang, Yu, Lei, Liao, Huaming, Fan, Yixing, Guo, Jiafeng, Cheng, Xueqi
Generative LLM have achieved remarkable success in various industrial applications, owing to their promising In-Context Learning capabilities. However, the issue of long context in complex tasks poses a significant barrier to their wider adoption, ma
Externí odkaz:
http://arxiv.org/abs/2408.10497
Autor:
Ding Shunli, Cai Mengqi, Tian Bowen, Liang Junhao, Zhou Linshu, Wu Chuan, Huang Hanjie, Liu Jun
Publikováno v:
Frontiers in Energy Research, Vol 9 (2022)
In this article, the numerical model of the multi-span iced eight-bundle conductor is established using the nonlinear finite element method, the galloping of the line under different parameters is simulated, and the tension in the galloping process i
Externí odkaz:
https://doaj.org/article/e594c71143534eda8196c1bd8a3e0925
Generative adversarial networks (GANs) are known for their strong abilities on capturing the underlying distribution of training instances. Since the seminal work of GAN, many variants of GAN have been proposed. However, existing GANs are almost esta
Externí odkaz:
http://arxiv.org/abs/2302.01722
Anomaly Detection by Leveraging Incomplete Anomalous Knowledge with Anomaly-Aware Bidirectional GANs
The goal of anomaly detection is to identify anomalous samples from normal ones. In this paper, a small number of anomalies are assumed to be available at the training stage, but they are assumed to be collected only from several anomaly types, leavi
Externí odkaz:
http://arxiv.org/abs/2204.13335
Publikováno v:
In Reliability Engineering and System Safety November 2024 251
Autor:
Ren, Jianfei, Zhang, Jiying, Tian, Bowen, Pan, Zilong, Wang, Shan, Chen, Hongyun, He, Kaihua, Zhong, Hongxia, Wang, Qingbo
Publikováno v:
In International Journal of Hydrogen Energy 18 October 2024 87:554-565
Publikováno v:
In Advanced Engineering Informatics October 2024 62 Part B