Zobrazeno 1 - 10
of 3 090
pro vyhledávání: '"Xiong Jing"'
Autor:
XIONG Jing, WANG Wei
Publikováno v:
Chinese Journal of Contemporary Neurology and Neurosurgery, Vol 23, Iss 11, Pp 1018-1025 (2023)
Objective To analyze the clinical characteristics of 2 young patients with cerebral microhemorrhage as the main manifestation of cerebral small vessel disease (CSVD), and explore the relationship between the cerebral microhemorrhage and cognitive dys
Externí odkaz:
https://doaj.org/article/69858f2b5ccb491bbe6c6749b9a867c1
Publikováno v:
Liang you shipin ke-ji, Vol 31, Iss 4, Pp 55-62 (2023)
In this study, different sugar alcohols (maltitol, erythritol, xylitol, sorbitol) were added to make low sugar orange sweet potato puree. The effects of different sugar alcohols on rheological properties, storage color, β-carotene content and digest
Externí odkaz:
https://doaj.org/article/4937948394674b2dbfadc3b7c33a812a
Publikováno v:
Shipin gongye ke-ji, Vol 43, Iss 23, Pp 318-327 (2022)
Targeted at the aged Fengxiang crude Baijiu stored in Jiuhai, a container for Chinese Baijiu, this paper adopted the gas chromatography-mass spectrometry (GC-MS) and gas chromatography-ion mobility spectrometry (GC-IMS) to analyze the changes of vola
Externí odkaz:
https://doaj.org/article/0b72238d5dc846d0a3e61f4c6d20b67f
Autor:
Chen Bin, Xiong Jing
Publikováno v:
E3S Web of Conferences, Vol 512, p 01002 (2024)
The study aims to analyze the evolution trend of system vulnerability under the interactive relationship of building construction risk factors. Based on social technology theory, the influencing factors are analyzed from four subsystems: individual,
Externí odkaz:
https://doaj.org/article/21ce70648345454aa27839281cc4d9f6
Autor:
Lesly Dasilva Wandji Djouonkep, Zhengzai Cheng, William Mawuko Kodjo Siegu, Xiong Jing, Jun Chen, Elvis Kwame Adom, Abubakar Muaz, Mario Gauthier
Publikováno v:
eXPRESS Polymer Letters, Vol 16, Iss 1, Pp 102-114 (2022)
In this investigation, a series of novel random bio-based thiophene–aromatic copolyesters, including thiophene and phenyl units, were successfully prepared from dimethyl 2,5-thiophenedicarboxylate, dimethyl 2,5-dimethoxyterephthalate, and the aliph
Externí odkaz:
https://doaj.org/article/fdd81c94a99342789d8b1dfa9aaa2857
Autor:
Xiong, Jing, Liu, Gongye, Huang, Lun, Wu, Chengyue, Wu, Taiqiang, Mu, Yao, Yao, Yuan, Shen, Hui, Wan, Zhongwei, Huang, Jinfa, Tao, Chaofan, Yan, Shen, Yao, Huaxiu, Kong, Lingpeng, Yang, Hongxia, Zhang, Mi, Sapiro, Guillermo, Luo, Jiebo, Luo, Ping, Wong, Ngai
Autoregressive modeling has been a huge success in the field of natural language processing (NLP). Recently, autoregressive models have emerged as a significant area of focus in computer vision, where they excel in producing high-quality visual conte
Externí odkaz:
http://arxiv.org/abs/2411.05902
Autoformalization aims to convert informal mathematical proofs into machine-verifiable formats, bridging the gap between natural and formal languages. However, ensuring semantic alignment between the informal and formalized statements remains challen
Externí odkaz:
http://arxiv.org/abs/2410.10135
Autor:
Zheng, Chuanyang, Gao, Yihang, Shi, Han, Xiong, Jing, Sun, Jiankai, Li, Jingyao, Huang, Minbin, Ren, Xiaozhe, Ng, Michael, Jiang, Xin, Li, Zhenguo, Li, Yu
The attention mechanism is a fundamental component of the Transformer model, contributing to interactions among distinct tokens, in contrast to earlier feed-forward neural networks. In general, the attention scores are determined simply by the key-qu
Externí odkaz:
http://arxiv.org/abs/2410.04798
Autor:
Xiong, Jing, Shen, Jianghan, Ye, Fanghua, Tao, Chaofan, Wan, Zhongwei, Lu, Jianqiao, Wu, Xun, Zheng, Chuanyang, Guo, Zhijiang, Kong, Lingpeng, Wong, Ngai
Deploying large language models (LLMs) is challenging due to their high memory and computational demands, especially during long-context inference. While key-value (KV) caching accelerates inference by reusing previously computed keys and values, it
Externí odkaz:
http://arxiv.org/abs/2410.03090
Autor:
Li, Zixuan, Xiong, Jing, Ye, Fanghua, Zheng, Chuanyang, Wu, Xun, Lu, Jianqiao, Wan, Zhongwei, Liang, Xiaodan, Li, Chengming, Sun, Zhenan, Kong, Lingpeng, Wong, Ngai
We present UncertaintyRAG, a novel approach for long-context Retrieval-Augmented Generation (RAG) that utilizes Signal-to-Noise Ratio (SNR)-based span uncertainty to estimate similarity between text chunks. This span uncertainty enhances model calibr
Externí odkaz:
http://arxiv.org/abs/2410.02719