Zobrazeno 1 - 10
of 151
pro vyhledávání: '"Tu, Zhiying"'
Autor:
Qin, Zhanyue, Wang, Haochuan, Wang, Zecheng, Liu, Deyuan, Fan, Cunhang, Lv, Zhao, Tu, Zhiying, Chu, Dianhui, Sui, Dianbo
In recent years, with the maturation of large language model (LLM) technology and the emergence of high-quality programming code datasets, researchers have become increasingly confident in addressing the challenges of program synthesis automatically.
Externí odkaz:
http://arxiv.org/abs/2410.07820
Large Language Model (LLM) services exhibit impressive capability on unlearned tasks leveraging only a few examples by in-context learning (ICL). However, the success of ICL varies depending on the task and context, leading to heterogeneous service q
Externí odkaz:
http://arxiv.org/abs/2410.07737
The unique diagnosis and treatment techniques and remarkable clinical efficacy of traditional Chinese medicine (TCM) make it play an important role in the field of elderly care and healthcare, especially in the rehabilitation of some common chronic d
Externí odkaz:
http://arxiv.org/abs/2408.00481
Autor:
Qin, Zhanyue, Wang, Haochuan, Liu, Deyuan, Song, Ziyang, Fan, Cunhang, Lv, Zhao, Wu, Jinlin, Lei, Zhen, Tu, Zhiying, Chu, Dianhui, Yu, Xiaoyan, Sui, Dianbo
Sequential decision-making refers to algorithms that take into account the dynamics of the environment, where early decisions affect subsequent decisions. With large language models (LLMs) demonstrating powerful capabilities between tasks, we can't h
Externí odkaz:
http://arxiv.org/abs/2406.16382
Autor:
Liu, Deyuan, Qin, Zhanyue, Wang, Hairu, Yang, Zhao, Wang, Zecheng, Rong, Fangying, Liu, Qingbin, Hao, Yanchao, Chen, Xi, Fan, Cunhang, Lv, Zhao, Tu, Zhiying, Chu, Dianhui, Li, Bo, Sui, Dianbo
While large language models (LLMs) excel in many domains, their complexity and scale challenge deployment in resource-limited environments. Current compression techniques, such as parameter pruning, often fail to effectively utilize the knowledge fro
Externí odkaz:
http://arxiv.org/abs/2406.16330
Microservice architecture has become a dominant architectural style in the service-oriented software industry. Poor practices in the design and development of microservices are called microservice bad smells. In microservice bad smells research, the
Externí odkaz:
http://arxiv.org/abs/2404.01789
Autor:
Liu, Deyuan, Wang, Zecheng, Wang, Bingning, Chen, Weipeng, Li, Chunshan, Tu, Zhiying, Chu, Dianhui, Li, Bo, Sui, Dianbo
The rapid proliferation of large language models (LLMs) such as GPT-4 and Gemini underscores the intense demand for resources during their training processes, posing significant challenges due to substantial computational and environmental costs. To
Externí odkaz:
http://arxiv.org/abs/2403.19390
Language models as a service (LMaaS) enable users to accomplish tasks without requiring specialized knowledge, simply by paying a service provider. However, numerous providers offer massive large language model (LLM) services with variations in laten
Externí odkaz:
http://arxiv.org/abs/2402.03408
Using natural language, Conversational Bot offers unprecedented ways to many challenges in areas such as information searching, item recommendation, and question answering. Existing bots are usually developed through retrieval-based or generative-bas
Externí odkaz:
http://arxiv.org/abs/2301.12400
Temporal graph neural network has recently received significant attention due to its wide application scenarios, such as bioinformatics, knowledge graphs, and social networks. There are some temporal graph neural networks that achieve remarkable resu
Externí odkaz:
http://arxiv.org/abs/2301.08399