Zobrazeno 1 - 10
of 1 342
pro vyhledávání: '"Han Jiawei"'
Publikováno v:
智慧农业, Vol 6, Iss 4, Pp 138-148 (2024)
ObjectiveThe dynamic prediction of carbon emission from cold chain distribution is an important basis for the accurate assessment of carbon emission and its green credit grade. Facing the fact that the carbon emission of vehicles is affected by multi
Externí odkaz:
https://doaj.org/article/bd4fe54071b14fb58baaca6bba747710
Publikováno v:
智慧农业, Vol 5, Iss 1, Pp 22-33 (2023)
The new generation of information technology has led to the rapid development of the intelligent level of the cold chain, and the precise control of the development level of the smart cold chain is the prerequisite foundation and guarantee to achieve
Externí odkaz:
https://doaj.org/article/3a713745dcf44c24b065165b856b9238
Publikováno v:
智慧农业, Vol 5, Iss 1, Pp 44-51 (2023)
In recent years, China's cold chain logistics industry has entered a stage of rapid development. At the same time, with the increase of greenhouse gas emissions, green and low-carbon transformation has become a new feature and direction of high-quali
Externí odkaz:
https://doaj.org/article/f34a0ba0f41e4d709a3e572ce43cfb53
Publikováno v:
中国工程科学, Vol 24, Iss 1, Pp 55-63 (2022)
Agricultural machinery and equipment is the material basis of modern agricultural development and an important symbol of agricultural mechanization. The new generation of information technology can drive the intelligent transformation and upgrading o
Externí odkaz:
https://doaj.org/article/ec06f72540df4ffbac920f9842996712
Publikováno v:
中国工程科学, Vol 23, Iss 4, Pp 30-36 (2021)
The lagging informatization and intellectualization of the agricultural product postharvest supply chain is the main factor that results in low circulation efficiency and serious quality loss. Improvement on the postharvest added values of agricultur
Externí odkaz:
https://doaj.org/article/1028abebc315498d99d88f0771daf334
Autor:
Ouyang, Siru, Wang, Shuohang, Jiang, Minhao, Zhong, Ming, Yu, Donghan, Han, Jiawei, Shen, Yelong
Speculative decoding stands as a pivotal technique to expedite inference in autoregressive (large) language models. This method employs a smaller draft model to speculate a block of tokens, which the target model then evaluates for acceptance. Despit
Externí odkaz:
http://arxiv.org/abs/2410.10141
Publikováno v:
NeurIPs 2024
In this paper, we approach an overlooked yet critical task Graph2Image: generating images from multimodal attributed graphs (MMAGs). This task poses significant challenges due to the explosion in graph size, dependencies among graph entities, and the
Externí odkaz:
http://arxiv.org/abs/2410.07157
Retrieval-augmented generation (RAG) empowers large language models (LLMs) to utilize external knowledge sources. The increasing capacity of LLMs to process longer input sequences opens up avenues for providing more retrieved information, to potentia
Externí odkaz:
http://arxiv.org/abs/2410.05983
Autor:
Jiang, Pengcheng, Xiao, Cao, Jiang, Minhao, Bhatia, Parminder, Kass-Hout, Taha, Sun, Jimeng, Han, Jiawei
Large language models (LLMs) have demonstrated significant potential in clinical decision support. Yet LLMs still suffer from hallucinations and lack fine-grained contextual medical knowledge, limiting their high-stake healthcare applications such as
Externí odkaz:
http://arxiv.org/abs/2410.04585
Training and serving long-context large language models (LLMs) incurs substantial overhead. To address this, two critical steps are often required: a pretrained LLM typically undergoes a separate stage for context length extension by training on long
Externí odkaz:
http://arxiv.org/abs/2410.01485