Zobrazeno 1 - 10
of 397
pro vyhledávání: '"Wang Weixuan"'
Autor:
WANG Weixuan, TIAN Shuangqi, KE Jin, ZHANG Fan, CHENG Yuanzhi, CHEN Xiaoquan, LI Hongyou, SHI Taoxiong, CHEN Qingfu
Publikováno v:
Guangxi Zhiwu, Vol 44, Iss 2, Pp 291-302 (2024)
Fagopyrum tatari-cymosum is a semi-perennial new buckwheat type developped from the hybridization between F. tataricum and F. cymosum. To explore the genetic laws of agronomic and quality traits of F. tatari-cymosum, 26 lines of F. tatari-cymosum wer
Externí odkaz:
https://doaj.org/article/b6735ee6f7234dd981dcdae6b49e4638
Large language models (LLMs) have revolutionized the field of natural language processing (NLP), and recent studies have aimed to understand their underlying mechanisms. However, most of this research is conducted within a monolingual setting, primar
Externí odkaz:
http://arxiv.org/abs/2406.09265
Autor:
Wang Weixuan
Publikováno v:
E3S Web of Conferences, Vol 352, p 01004 (2022)
In order to solve the problems of unclear division of the delta front pre delta facies belt of the first member of Qing Dynasty in Hei-258 area of Daqingzijing in the south of Songliao Basin and the lack of a unified fine isochronous stratigraphic fr
Externí odkaz:
https://doaj.org/article/5d0f739345e54fbfb4ec58437a616b2e
Autor:
Gao, Yiming, Liu, Feiyu, Wang, Liang, Lian, Zhenjie, Zheng, Dehua, Wang, Weixuan, Yang, Wenjin, Li, Siqin, Wang, Xianliang, Chen, Wenhui, Dai, Jing, Fu, Qiang, Yang, Wei, Huang, Lanxiao, Liu, Wei
Existing game AI research mainly focuses on enhancing agents' abilities to win games, but this does not inherently make humans have a better experience when collaborating with these agents. For example, agents may dominate the collaboration and exhib
Externí odkaz:
http://arxiv.org/abs/2401.16444
Knowledge represented in Large Language Models (LLMs) is quite often incorrect and can also become obsolete over time. Updating knowledge via fine-tuning is computationally resource-hungry and not reliable, and so knowledge editing (KE) has developed
Externí odkaz:
http://arxiv.org/abs/2312.13040
Large language models (LLMs) have been treated as knowledge bases due to their strong performance in knowledge probing tasks. LLMs are typically evaluated using accuracy, yet this metric does not capture the vulnerability of LLMs to hallucination-ind
Externí odkaz:
http://arxiv.org/abs/2310.09820
Autor:
Ishtiaq, Abdullah Al, Das, Sarkar Snigdha Sarathi, Rashid, Syed Md Mukit, Ranjbar, Ali, Tu, Kai, Wu, Tianwei, Song, Zhezheng, Wang, Weixuan, Akon, Mujtahid, Zhang, Rui, Hussain, Syed Rafiul
In this paper, we present Hermes, an end-to-end framework to automatically generate formal representations from natural language cellular specifications. We first develop a neural constituency parser, NEUTREX, to process transition-relevant texts and
Externí odkaz:
http://arxiv.org/abs/2310.04381
Length-controllable machine translation is a type of constrained translation. It aims to contain the original meaning as much as possible while controlling the length of the translation. We can use automatic summarization or machine translation evalu
Externí odkaz:
http://arxiv.org/abs/2305.02300
Autor:
Gao, Yiming, Liu, Feiyu, Wang, Liang, Lian, Zhenjie, Wang, Weixuan, Li, Siqin, Wang, Xianliang, Zeng, Xianhan, Wang, Rundong, Wang, Jiawei, Fu, Qiang, Yang, Wei, Huang, Lanxiao, Liu, Wei
MOBA games, e.g., Dota2 and Honor of Kings, have been actively used as the testbed for the recent AI research on games, and various AI systems have been developed at the human level so far. However, these AI systems mainly focus on how to compete wit
Externí odkaz:
http://arxiv.org/abs/2304.11632
Homographs, words with the same spelling but different meanings, remain challenging in Neural Machine Translation (NMT). While recent works leverage various word embedding approaches to differentiate word sense in NMT, they do not focus on the pivota
Externí odkaz:
http://arxiv.org/abs/2304.05860