Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Gao, Ze-Feng"'
Symbolic regression plays a crucial role in modern scientific research thanks to its capability of discovering concise and interpretable mathematical expressions from data. A grand challenge lies in the arduous search for parsimonious and generalizab
Externí odkaz:
http://arxiv.org/abs/2407.04405
Autor:
Zhu, Yutao, Zhou, Kun, Mao, Kelong, Chen, Wentong, Sun, Yiding, Chen, Zhipeng, Cao, Qian, Wu, Yihan, Chen, Yushuo, Wang, Feng, Zhang, Lei, Li, Junyi, Wang, Xiaolei, Wang, Lei, Zhang, Beichen, Dong, Zican, Cheng, Xiaoxue, Chen, Yuhan, Tang, Xinyu, Hou, Yupeng, Ren, Qiangqiang, Pang, Xincheng, Xie, Shufang, Zhao, Wayne Xin, Dou, Zhicheng, Mao, Jiaxin, Lin, Yankai, Song, Ruihua, Xu, Jun, Chen, Xu, Yan, Rui, Wei, Zhewei, Hu, Di, Huang, Wenbing, Gao, Ze-Feng, Chen, Yueguo, Lu, Weizheng, Wen, Ji-Rong
Large language models (LLMs) have become the foundation of many applications, leveraging their extensive capabilities in processing and understanding natural language. While many open-source LLMs have been released with technical reports, the lack of
Externí odkaz:
http://arxiv.org/abs/2406.19853
Magnetism and topology are two major areas of condensed matter physics. The combination of magnetism and topology gives rise to more novel physical effects, which have attracted strongly theoretical and experimental attention. Recently, the concept o
Externí odkaz:
http://arxiv.org/abs/2406.16603
Key-value~(KV) caching is an important technique to accelerate the inference of large language models~(LLMs), but incurs significant memory overhead. To compress the size of KV cache, existing methods often compromise precision or require extra data
Externí odkaz:
http://arxiv.org/abs/2405.12591
Spin-orbit coupling is a key to realize many novel physical effects in condensed matter physics, but the mechanism to achieve strong spin-orbit coupling effect in light element antiferromagnetic compounds has not been explored. In this work, based on
Externí odkaz:
http://arxiv.org/abs/2401.11065
Altermagnetism is a new magnetic phase with k-dependent spin polarization and may exist in an insulating state with a high N\'eel temperature. This provides a new opportunity to obtain both spin and electric polarization in one material. Here, based
Externí odkaz:
http://arxiv.org/abs/2312.13911
Autor:
Gao, Ze-Feng, Qu, Shuai, Zeng, Bocheng, Liu, Yang, Wen, Ji-Rong, Sun, Hao, Guo, Peng-Jie, Lu, Zhong-Yi
Altermagnetism, a new magnetic phase, has been theoretically proposed and experimentally verified to be distinct from ferromagnetism and antiferromagnetism. Although altermagnets have been found to possess many exotic physical properties, the very li
Externí odkaz:
http://arxiv.org/abs/2311.04418
Autor:
Liu, Peiyu, Liu, Zikang, Gao, Ze-Feng, Gao, Dawei, Zhao, Wayne Xin, Li, Yaliang, Ding, Bolin, Wen, Ji-Rong
Despite the superior performance, Large Language Models~(LLMs) require significant computational resources for deployment and use. To overcome this issue, quantization methods have been widely applied to reduce the memory footprint of LLMs as well as
Externí odkaz:
http://arxiv.org/abs/2307.08072
In this paper, we propose a highly parameter-efficient approach to scaling pre-trained language models (PLMs) to a deeper model depth. Unlike prior work that shares all parameters or uses extra blocks, we design a more capable parameter-sharing archi
Externí odkaz:
http://arxiv.org/abs/2303.16753
Publikováno v:
COLING2022 Oral Presentation
Recently, Mixture-of-Experts (short as MoE) architecture has achieved remarkable success in increasing the model capacity of large-scale language models. However, MoE requires incorporating significantly more parameters than the base model being exte
Externí odkaz:
http://arxiv.org/abs/2203.01104