Zobrazeno 1 - 10
of 213
pro vyhledávání: '"HU Mengting"'
Autor:
HU Mengting, ZHANG Dong, JIA Peiyao, LU Minya, ZHOU Menglan, GUO Jiayu, SU Huiting, GAO Yi, XI Jingyuan, ZHU Huadong, YANG Qiwen
Publikováno v:
Xiehe Yixue Zazhi, Vol 15, Iss 6, Pp 1463-1467 (2024)
We report a case of a male patient who developed persistent fever and central nervous system symptoms after eating raw snails for 10 days. The patient was diagnosed with Angiostrongyliasis depended on the clinical presentation, epidemiological histor
Externí odkaz:
https://doaj.org/article/5b2f49a6b70147a8a6a268f80a7135d6
Autor:
HU Mengting, CHEN Junxia
Publikováno v:
陆军军医大学学报, Vol 44, Iss 12, Pp 1207-1220 (2022)
Objective To explore the effects of the interaction between circular RNA hsa_circ_0000231 and HnRNPK on the proliferation, migration and apoptosis in breast cancer. Methods Microarray analysis was used to investigate the expression profile of circRNA
Externí odkaz:
https://doaj.org/article/4a6f93e862cd49829a3419f1eae01c13
Autor:
Zhang, Zhen, Wang, Xinyu, Jiang, Yong, Chen, Zhuo, Mu, Feiteng, Hu, Mengting, Xie, Pengjun, Huang, Fei
Large Language Models (LLMs) are increasingly recognized for their practical applications. However, these models often encounter challenges in dynamically changing knowledge, as well as in managing unknown static knowledge. Retrieval-Augmented Genera
Externí odkaz:
http://arxiv.org/abs/2411.06207
Autor:
Ying, Rui, Hu, Mengting, Wu, Jianfeng, Xie, Yalan, Liu, Xiaoyi, Wang, Zhunheng, Jiang, Ming, Gao, Hang, Zhang, Linlin, Cheng, Renhong
Temporal knowledge graph completion aims to infer the missing facts in temporal knowledge graphs. Current approaches usually embed factual knowledge into continuous vector space and apply geometric operations to learn potential patterns in temporal k
Externí odkaz:
http://arxiv.org/abs/2408.06603
Autor:
Wang, Xunzhi, Zhang, Zhuowei, Li, Qiongyu, Chen, Gaonan, Hu, Mengting, li, Zhiyu, Luo, Bitong, Gao, Hang, Han, Zhixin, Wang, Haotian
The rapid development of large language models (LLMs) has shown promising practical results. However, their low interpretability often leads to errors in unforeseen circumstances, limiting their utility. Many works have focused on creating comprehens
Externí odkaz:
http://arxiv.org/abs/2406.12784
Autor:
Bai, Yinhao, Xie, Yalan, Liu, Xiaoyi, Zhao, Yuhua, Han, Zhixin, Hu, Mengting, Gao, Hang, Cheng, Renhong
Aspect sentiment quad prediction (ASQP) aims to predict four aspect-based elements, including aspect term, opinion term, aspect category, and sentiment polarity. In practice, unseen aspects, due to distinct data distribution, impose many challenges f
Externí odkaz:
http://arxiv.org/abs/2406.07365
Autor:
Gong, Cheng, Zheng, Haoshuai, Hu, Mengting, Lin, Zheng, Fan, Deng-Ping, Zhang, Yuzhi, Li, Tao
Publikováno v:
CAAI Artificial Intelligence Research, 2024
Quantization is a promising method that reduces memory usage and computational intensity of Deep Neural Networks (DNNs), but it often leads to significant output error that hinder model deployment. In this paper, we propose Bias Compensation (BC) to
Externí odkaz:
http://arxiv.org/abs/2404.01892
Autor:
Chen, Zhuang, Wu, Jincenzi, Zhou, Jinfeng, Wen, Bosi, Bi, Guanqun, Jiang, Gongyao, Cao, Yaru, Hu, Mengting, Lai, Yunghwei, Xiong, Zexuan, Huang, Minlie
Theory of Mind (ToM) is the cognitive capability to perceive and ascribe mental states to oneself and others. Recent research has sparked a debate over whether large language models (LLMs) exhibit a form of ToM. However, existing ToM evaluations are
Externí odkaz:
http://arxiv.org/abs/2402.15052
Autor:
Liang, Xun, Wang, Hanyu, Song, Shichao, Hu, Mengting, Wang, Xunzhi, Li, Zhiyu, Xiong, Feiyu, Tang, Bo
Controlled Text Generation (CTG) aims to produce texts that exhibit specific desired attributes. In this study, we introduce a pluggable CTG framework for Large Language Models (LLMs) named Dynamic Attribute Graphs-based controlled text generation (D
Externí odkaz:
http://arxiv.org/abs/2402.11218
Named Entity Recognition (NER) serves as a fundamental task in natural language understanding, bearing direct implications for web content analysis, search engines, and information retrieval systems. Fine-tuned NER models exhibit satisfactory perform
Externí odkaz:
http://arxiv.org/abs/2402.10573