Zobrazeno 1 - 10
of 553
pro vyhledávání: '"XU Jiahao"'
Research on carbon reduction transformation in industrial processes based on carbon handprint method
Publikováno v:
Zhejiang dianli, Vol 43, Iss 3, Pp 122-129 (2024)
To address the ambiguity surrounding methods and standards for reducing carbon emissions in industrial processes， it is essential to quantitatively assess the impact of carbon emissions and formulate a scientifically grounded carbon reduction plan.
Externí odkaz:
https://doaj.org/article/877c28d87eb64fe68b3a72bb0828cc77
Publikováno v:
Cailiao gongcheng, Vol 50, Iss 9, Pp 105-112 (2022)
TiC reinforced high chromium cast iron(HCCI) matrix composites were prepared by high energy ball milling and vacuum sintering.Scanning electron microscope (SEM) and differential scanning calorimetry (DSC) were employed to analyze the powder at differ
Externí odkaz:
https://doaj.org/article/c7b0c78375cb4a19af41995de21e7fc4
Backdoor attacks present a significant threat to the robustness of Federated Learning (FL) due to their stealth and effectiveness. They maintain both the main task of the FL system and the backdoor task simultaneously, causing malicious models to app
Externí odkaz:
http://arxiv.org/abs/2411.01040
Foundation models (FMs) have shown remarkable advancements in enhancing the performance of intelligent applications. To address the need for data privacy in FM fine-tuning, federated learning has emerged as the de facto framework. Specifically, Feder
Externí odkaz:
http://arxiv.org/abs/2410.10200
Federated Learning (FL) enables multiple clients to collaboratively train a model without sharing their local data. Yet the FL system is vulnerable to well-designed Byzantine attacks, which aim to disrupt the model training process by uploading malic
Externí odkaz:
http://arxiv.org/abs/2409.01435
Autor:
Yuan, Youliang, Jiao, Wenxiang, Wang, Wenxuan, Huang, Jen-tse, Xu, Jiahao, Liang, Tian, He, Pinjia, Tu, Zhaopeng
This study addresses a critical gap in safety tuning practices for Large Language Models (LLMs) by identifying and tackling a refusal position bias within safety tuning data, which compromises the models' ability to appropriately refuse generating un
Externí odkaz:
http://arxiv.org/abs/2407.09121
We designed a multilayered self-adaptive absorber/emitter metamaterial, which can smartly switch between a solar absorber and a radiative cooler based on temperature change. The switching capability is facilitated by the phase change material and the
Externí odkaz:
http://arxiv.org/abs/2407.02050
Autor:
Mei, Shuhao, Li, Xin, Zhou, Yuxi, Xu, Jiahao, Zhang, Yong, Wan, Yuxuan, Cao, Shan, Zhao, Qinghao, Geng, Shijia, Xie, Junqing, Chen, Shengyong, Hong, Shenda
Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung disease that causes airflow obstruction. Current methods can only detect COPD from prominent features in spirogram (Volume-Flow time series) but cannot predict future COPD risk from subtl
Externí odkaz:
http://arxiv.org/abs/2405.03239
Under circumstances of heterophily, where nodes with different labels tend to be connected based on semantic meanings, Graph Neural Networks (GNNs) often exhibit suboptimal performance. Current studies on graph heterophily mainly focus on aggregation
Externí odkaz:
http://arxiv.org/abs/2403.17351
Publikováno v:
In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 419--430, Seattle, United States. Association for Computational Linguistics
Back translation (BT) is one of the most significant technologies in NMT research fields. Existing attempts on BT share a common characteristic: they employ either beam search or random sampling to generate synthetic data with a backward model but se
Externí odkaz:
http://arxiv.org/abs/2310.13675