Zobrazeno 1 - 10
of 2 125
pro vyhledávání: '"Chen Bei"'
Publikováno v:
Redai dili, Vol 44, Iss 10, Pp 1787-1799 (2024)
Within the broader context of China's industrial structural transformation, the spillover effects of environmental regulations on urban industrial structure upgrading have gained increasing attention. This study uses panel data from 260 prefecture-le
Externí odkaz:
https://doaj.org/article/43558880f2ac4538bc58bad242e1ebbf
Publikováno v:
能源环境保护, Vol 37, Iss 6, Pp 119-128 (2023)
Numerical simulation was conducted to investigate the heat and mass transfer characteristics in a 12 t/d pilot-scale grate-type incinerator for municipal solid waste during the co-incineration of industrial solid waste, and the velocity field, temper
Externí odkaz:
https://doaj.org/article/8a5a2eeb192f4d4980f462a6ad82ef83
Publikováno v:
Nonlinear Engineering, Vol 12, Iss 1, Pp 033001-104 (2023)
In this article, the sensitivity coefficients of dynamic characteristic damage identification of blades with different sizes were investigated. The results show that the first third-order vibration modes of the blade before and after damage are consi
Externí odkaz:
https://doaj.org/article/97954917cd064671ae5f958b8036ff96
Autor:
AI, 01., Wake, Alan, Wang, Albert, Chen, Bei, Lv, C. X., Li, Chao, Huang, Chengen, Cai, Chenglin, Zheng, Chujie, Cooper, Daniel, Dai, Ethan, Zhou, Fan, Hu, Feng, Ji, Heng, Qiu, Howard, Zhu, Jiangcheng, Tian, Jun, Su, Katherine, Zhang, Lihuan, Li, Liying, Song, Ming, Li, Mou, Liu, Peng, Hu, Qicheng, Wang, Shawn, Zhou, Shijun, Li, Shiyong, Zhu, Tianhang, Xie, Wen, He, Xiang, Chen, Xiaobo, Hu, Xiaohui, Ren, Xiaoyi, Niu, Xinyao, Li, Yanpeng, Zhao, Yongke, Luo, Yongzhen, Xu, Yuchi, Sha, Yuxuan, Yan, Zhaodong, Liu, Zhiyuan, Zhang, Zirui
This technical report presents Yi-Lightning, our latest flagship large language model (LLM). It achieves exceptional performance, ranking 6th overall on Chatbot Arena, with particularly strong results (2nd to 4th place) in specialized categories incl
Externí odkaz:
http://arxiv.org/abs/2412.01253
Autor:
Zhang, Fengji, Wu, Linquan, Bai, Huiyu, Lin, Guancheng, Li, Xiao, Yu, Xiao, Wang, Yue, Chen, Bei, Keung, Jacky
Coding tasks have been valuable for evaluating Large Language Models (LLMs), as they demand the comprehension of high-level instructions, complex reasoning, and the implementation of functional programs -- core capabilities for advancing Artificial G
Externí odkaz:
http://arxiv.org/abs/2410.12381
Autor:
Li, Dongxu, Liu, Yudong, Wu, Haoning, Wang, Yue, Shen, Zhiqi, Qu, Bowen, Niu, Xinyao, Wang, Guoyin, Chen, Bei, Li, Junnan
Information comes in diverse modalities. Multimodal native AI models are essential to integrate real-world information and deliver comprehensive understanding. While proprietary multimodal native models exist, their lack of openness imposes obstacles
Externí odkaz:
http://arxiv.org/abs/2410.05993
Scientific leaderboards are standardized ranking systems that facilitate evaluating and comparing competitive methods. Typically, a leaderboard is defined by a task, dataset, and evaluation metric (TDM) triple, allowing objective performance assessme
Externí odkaz:
http://arxiv.org/abs/2409.12656
Addressing critical challenges in Lamb wave resonators, this paper presents the first validation of resonators incorporating sub-wavelength through-holes. Using the A3 mode resonator based on a LiNbO3 single-crystal thin film and operating in the K b
Externí odkaz:
http://arxiv.org/abs/2409.00783
Large multimodal models (LMMs) are processing increasingly longer and richer inputs. Albeit the progress, few public benchmark is available to measure such development. To mitigate this gap, we introduce LongVideoBench, a question-answering benchmark
Externí odkaz:
http://arxiv.org/abs/2407.15754
Autor:
Wang, Junjie, Zhang, Yin, Ji, Yatai, Zhang, Yuxiang, Jiang, Chunyang, Wang, Yubo, Zhu, Kang, Wang, Zekun, Wang, Tiezhen, Huang, Wenhao, Fu, Jie, Chen, Bei, Lin, Qunshu, Liu, Minghao, Zhang, Ge, Chen, Wenhu
Recent advancements in Large Multimodal Models (LMMs) have leveraged extensive multimodal datasets to enhance capabilities in complex knowledge-driven tasks. However, persistent challenges in perceptual and reasoning errors limit their efficacy, part
Externí odkaz:
http://arxiv.org/abs/2406.13923