Zobrazeno 1 - 10
of 1 461
pro vyhledávání: '"Yu Xiaoyan"'
Publikováno v:
电力工程技术, Vol 42, Iss 6, Pp 91-99 (2023)
With the integration of large-scale photovoltaic power stations into power grids, the traditional strategy of the backup automatic switch is affected. When a grid fault occurs, due to the existence of photovoltaic power sources, the busbar voltage at
Externí odkaz:
https://doaj.org/article/277d1a53c36b4cea83213cc81697326a
Large language models encapsulate knowledge and have demonstrated superior performance on various natural language processing tasks. Recent studies have localized this knowledge to specific model parameters, such as the MLP weights in intermediate la
Externí odkaz:
http://arxiv.org/abs/2409.00617
Autor:
Yu, Xiaoyan, Wei, Yifan, Li, Pu, Zhou, Shuaishuai, Peng, Hao, Sun, Li, Zhu, Liehuang, Yu, Philip S.
Training social event detection models through federated learning (FedSED) aims to improve participants' performance on the task. However, existing federated learning paradigms are inadequate for achieving FedSED's objective and exhibit limitations i
Externí odkaz:
http://arxiv.org/abs/2409.00614
The use of a single image restoration framework to achieve multi-task image restoration has garnered significant attention from researchers. However, several practical challenges remain, including meeting the specific and simultaneous demands of diff
Externí odkaz:
http://arxiv.org/abs/2407.19139
Autor:
Peng, Kun, Jiang, Lei, Li, Qian, Li, Haoran, Yu, Xiaoyan, Sun, Li, Sun, Shuo, Bi, Yanxian, Peng, Hao
Cross-domain Aspect Sentiment Triplet Extraction (ASTE) aims to extract fine-grained sentiment elements from target domain sentences by leveraging the knowledge acquired from the source domain. Due to the absence of labeled data in the target domain,
Externí odkaz:
http://arxiv.org/abs/2407.21052
Autor:
Yang, Zhiwei, Wei, Yuecen, Li, Haoran, Li, Qian, Jiang, Lei, Sun, Li, Yu, Xiaoyan, Hu, Chunming, Peng, Hao
Social event detection refers to extracting relevant message clusters from social media data streams to represent specific events in the real world. Social event detection is important in numerous areas, such as opinion analysis, social safety, and d
Externí odkaz:
http://arxiv.org/abs/2407.18274
Heatmaps generated on inputs of image classification networks via explainable AI methods like Grad-CAM and LRP have been observed to resemble segmentations of input images in many cases. Consequently, heatmaps have also been leveraged for achieving w
Externí odkaz:
http://arxiv.org/abs/2407.03009
Autor:
Qin, Zhanyue, Wang, Haochuan, Liu, Deyuan, Song, Ziyang, Fan, Cunhang, Lv, Zhao, Wu, Jinlin, Lei, Zhen, Tu, Zhiying, Chu, Dianhui, Yu, Xiaoyan, Sui, Dianbo
Sequential decision-making refers to algorithms that take into account the dynamics of the environment, where early decisions affect subsequent decisions. With large language models (LLMs) demonstrating powerful capabilities between tasks, we can't h
Externí odkaz:
http://arxiv.org/abs/2406.16382
Autor:
Li, Pu, Yu, Xiaoyan, Peng, Hao, Xian, Yantuan, Wang, Linqin, Sun, Li, Zhang, Jingyun, Yu, Philip S.
Social Event Detection (SED) aims to identify significant events from social streams, and has a wide application ranging from public opinion analysis to risk management. In recent years, Graph Neural Network (GNN) based solutions have achieved state-
Externí odkaz:
http://arxiv.org/abs/2404.08263
Complex contagion phenomena, such as the spread of information or contagious diseases, often occur among the population due to higher-order interactions between individuals. Individuals who can be represented by nodes in a network may play different
Externí odkaz:
http://arxiv.org/abs/2404.01046