Zobrazeno 1 - 10
of 661
pro vyhledávání: '"YANG Zhicheng"'
Autor:
HAN Xiao, SONG Zhaojie, LI Peiyu, DENG Sen, SONG Yilei, ZHANG Yunfei, CAO Changxiao, YANG Zhicheng, WU Jiapeng
Publikováno v:
Youqi dizhi yu caishoulu, Vol 31, Iss 1, Pp 63-71 (2024)
The core pore structure of the target shale oil block was finely characterized using scanning electron microscopy， and a microscopic numerical model of the pore-scale core was constructed to elucidate the intrinsic mechanisms and the main controlli
Externí odkaz:
https://doaj.org/article/11c7c2e8aa704eaa8c42ef4b3dd4d89c
Autor:
Asmael Mohammed, Safaei Babak, Kalaf Omer, Zeeshan Qasim, Aldakheel Fadi, Nasir Tauqir, Yang Zhicheng
Publikováno v:
Nanotechnology Reviews, Vol 11, Iss 1, Pp 1408-1436 (2022)
In this review article, the joining of carbon fiber-reinforced polymer composite with metallic materials by using friction welding techniques was discussed and the effects of process parameters on the weld properties were evaluated. Major parameters
Externí odkaz:
https://doaj.org/article/16d2e05e36bc42c4bbecaff95abc273f
Publikováno v:
Nanotechnology Reviews, Vol 11, Iss 1, Pp 321-371 (2022)
Functionally graded porous (FGP) nanocomposites are the most promising materials among the manufacturing and materials sector due to their adjustable physical, mechanical, and operational properties for distinctive engineering applications for maximi
Externí odkaz:
https://doaj.org/article/7f5a59517f7c4c51a9c8950e52117497
Autor:
Li, Zhangpu, Zou, Changhong, Ma, Suxue, Yang, Zhicheng, Du, Chen, Tang, Youbao, Cao, Zhenjie, Zhang, Ning, Lai, Jui-Hsin, Lin, Ruei-Sung, Ni, Yuan, Sun, Xingzhi, Xiao, Jing, Hou, Jieke, Zhang, Kai, Han, Mei
The rocketing prosperity of large language models (LLMs) in recent years has boosted the prevalence of vision-language models (VLMs) in the medical sector. In our online medical consultation scenario, a doctor responds to the texts and images provide
Externí odkaz:
http://arxiv.org/abs/2409.17610
Autor:
Yang, Zhicheng, Wang, Yiwei, Huang, Yinya, Guo, Zhijiang, Shi, Wei, Han, Xiongwei, Feng, Liang, Song, Linqi, Liang, Xiaodan, Tang, Jing
Large language models (LLMs) have exhibited their problem-solving abilities in mathematical reasoning. Solving realistic optimization (OPT) problems in application scenarios requires advanced and applied mathematics ability. However, current OPT benc
Externí odkaz:
http://arxiv.org/abs/2407.09887
Autor:
Lu, Jianqiao, Wan, Yingjia, Liu, Zhengying, Huang, Yinya, Xiong, Jing, Liu, Chengwu, Shen, Jianhao, Jin, Hui, Zhang, Jipeng, Wang, Haiming, Yang, Zhicheng, Tang, Jing, Guo, Zhijiang
Autoformalization, the conversion of natural language mathematics into formal languages, offers significant potential for advancing mathematical reasoning. However, existing efforts are limited to formal languages with substantial online corpora and
Externí odkaz:
http://arxiv.org/abs/2406.01940
Autor:
Wang, Zihui, Wang, Zheng, Lyu, Lingjuan, Peng, Zhaopeng, Yang, Zhicheng, Wen, Chenglu, Yu, Rongshan, Wang, Cheng, Fan, Xiaoliang
Collaborative fairness stands as an essential element in federated learning to encourage client participation by equitably distributing rewards based on individual contributions. Existing methods primarily focus on adjusting gradient allocations amon
Externí odkaz:
http://arxiv.org/abs/2405.18291
Autor:
Wang, Haiming, Xin, Huajian, Liu, Zhengying, Li, Wenda, Huang, Yinya, Lu, Jianqiao, Yang, Zhicheng, Tang, Jing, Yin, Jian, Li, Zhenguo, Liang, Xiaodan
Recent advances in automated theorem proving leverages language models to explore expanded search spaces by step-by-step proof generation. However, such approaches are usually based on short-sighted heuristics (e.g., log probability or value function
Externí odkaz:
http://arxiv.org/abs/2405.14414
Autor:
Lin, Xiaohan, Cao, Qingxing, Huang, Yinya, Yang, Zhicheng, Liu, Zhengying, Li, Zhenguo, Liang, Xiaodan
Humans can develop new theorems to explore broader and more complex mathematical results. While current generative language models (LMs) have achieved significant improvement in automatically proving theorems, their ability to generate new or reusabl
Externí odkaz:
http://arxiv.org/abs/2405.06677
Autor:
Huang, Yinya, Hong, Ruixin, Zhang, Hongming, Shao, Wei, Yang, Zhicheng, Yu, Dong, Zhang, Changshui, Liang, Xiaodan, Song, Linqi
Publikováno v:
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (ACL 2024)
In this study, we delve into the realm of counterfactual reasoning capabilities of large language models (LLMs). Our primary objective is to cultivate the counterfactual thought processes within LLMs and rigorously assess these processes for their va
Externí odkaz:
http://arxiv.org/abs/2311.17438