Zobrazeno 1 - 10
of 5 179
pro vyhledávání: '"Liu Qun"'
Publikováno v:
应用气象学报, Vol 35, Iss 1, Pp 118-128 (2024)
As an important part of weather modification operation, the scientific effectiveness evaluation of artificial rainfall enhancement has gradually attracted attentions of government and public. In order to evaluate effects of artificial rainfall enhanc
Externí odkaz:
https://doaj.org/article/085074bf7cb14b639eb7ac8875703016
Publikováno v:
Redai dili, Vol 44, Iss 1, Pp 106-120 (2024)
Studies on leisure walking among older adults have received extensive attention from various areas such as public health, medicine/prevention, sports, geography, architecture, urban/transportation planning, and leisure, as they focus on various theme
Externí odkaz:
https://doaj.org/article/20f6d0327324408e95790cc60ad3873f
Publikováno v:
Nanotechnology Reviews, Vol 12, Iss 1, Pp 19988-99 (2023)
Wearable flexible strain sensors have attracted considerable attention in recent years, while it is still a significant challenge to fabricate wearable flexible strain sensors with high sensitivity and wide sensing range simultaneously. In this work,
Externí odkaz:
https://doaj.org/article/4ef517d6beb0456bab0ca66a2479d43f
Publikováno v:
Redai dili, Vol 42, Iss 6, Pp 902-915 (2022)
Housing has always been a hot issue in various disciplines. Only when people live in peace can they be happy to work and achieve sustainable economic and social development. In recent years, the construction of a large number of subsidized housing co
Externí odkaz:
https://doaj.org/article/67d2c063394647aba4893e52a042c2d7
Autor:
Huang, Mianqiu, Liu, Xiaoran, Zhou, Shaojun, Zhang, Mozhi, Tan, Chenkun, Wang, Pengyu, Guo, Qipeng, Xu, Zhe, Li, Linyang, Lei, Zhikai, Li, Linlin, Liu, Qun, Zhou, Yaqian, Qiu, Xipeng, Huang, Xuanjing
With the development of large language models (LLMs), the sequence length of these models continues to increase, drawing significant attention to long-context language models. However, the evaluation of these models has been primarily limited to thei
Externí odkaz:
http://arxiv.org/abs/2411.06899
Autor:
Wang, Zezhong, Zeng, Xingshan, Liu, Weiwen, Li, Liangyou, Wang, Yasheng, Shang, Lifeng, Jiang, Xin, Liu, Qun, Wong, Kam-Fai
Supervised fine-tuning (SFT) is a common method to enhance the tool calling capabilities of Large Language Models (LLMs), with the training data often being synthesized. The current data synthesis process generally involves sampling a set of tools, f
Externí odkaz:
http://arxiv.org/abs/2410.18447
The success of large language models (LLMs) has prompted efforts to integrate speech and audio data, aiming to create general foundation models capable of processing both textual and non-textual inputs. Recent advances, such as GPT-4o, highlight the
Externí odkaz:
http://arxiv.org/abs/2410.13268
Autor:
Xu, Kaishuai, Yu, Tiezheng, Hou, Wenjun, Cheng, Yi, Leong, Chak Tou, Li, Liangyou, Jiang, Xin, Shang, Lifeng, Liu, Qun, Li, Wenjie
Large Language Models (LLMs) have exhibited strong mathematical reasoning and computational prowess, tackling tasks ranging from basic arithmetic to advanced competition-level problems. However, frequently occurring subtle errors, such as miscalculat
Externí odkaz:
http://arxiv.org/abs/2410.06638
Meta learning has been widely used to exploit rich-resource source tasks to improve the performance of low-resource target tasks. Unfortunately, most existing meta learning approaches treat different source tasks equally, ignoring the relatedness of
Externí odkaz:
http://arxiv.org/abs/2409.19075
Autor:
Chen, Kai, Gou, Yunhao, Huang, Runhui, Liu, Zhili, Tan, Daxin, Xu, Jing, Wang, Chunwei, Zhu, Yi, Zeng, Yihan, Yang, Kuo, Wang, Dingdong, Xiang, Kun, Li, Haoyuan, Bai, Haoli, Han, Jianhua, Li, Xiaohui, Jin, Weike, Xie, Nian, Zhang, Yu, Kwok, James T., Zhao, Hengshuang, Liang, Xiaodan, Yeung, Dit-Yan, Chen, Xiao, Li, Zhenguo, Zhang, Wei, Liu, Qun, Yao, Jun, Hong, Lanqing, Hou, Lu, Xu, Hang
GPT-4o, an omni-modal model that enables vocal conversations with diverse emotions and tones, marks a milestone for omni-modal foundation models. However, empowering Large Language Models to perceive and generate images, texts, and speeches end-to-en
Externí odkaz:
http://arxiv.org/abs/2409.18042