Zobrazeno 1 - 10
of 7 077
pro vyhledávání: '"Shu, Jun"'
Large language models (LLMs) have shown impressive performance on downstream tasks by in-context learning (ICL), which heavily relies on the quality of demonstrations selected from a large set of annotated examples. Recent works claim that in-context
Externí odkaz:
http://arxiv.org/abs/2405.17264
Autor:
Gao, Chenqiang, Liu, Chuandong, Shu, Jun, Liu, Fangcen, Liu, Jiang, Yang, Luyu, Gao, Xinbo, Meng, Deyu
Current state-of-the-art (SOTA) 3D object detection methods often require a large amount of 3D bounding box annotations for training. However, collecting such large-scale densely-supervised datasets is notoriously costly. To reduce the cumbersome dat
Externí odkaz:
http://arxiv.org/abs/2403.02818
Brain tissue segmentation is essential for neuroscience and clinical studies. However, segmentation on longitudinal data is challenging due to dynamic brain changes across the lifespan. Previous researches mainly focus on self-supervision with regula
Externí odkaz:
http://arxiv.org/abs/2308.06774
Publikováno v:
Italian Journal of Pediatrics, Vol 50, Iss 1, Pp 1-10 (2024)
Abstract Background This study aims to analyse changes in urinary kidney injury markers in children with Mycoplasma pneumoniae pneumonia (MPP), investigate the risk factors for MPP-related acute kidney injury (AKI) and establish a model to predict MP
Externí odkaz:
https://doaj.org/article/0cc41418589c4a17a92e648b890eb36a
Autor:
Li-Jun Cao, Tian-Bo Guan, Jin-Cui Chen, Fangyuan Yang, Jing-Xian Liu, Feng-Liang Jin, Shu-Jun Wei
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-6 (2024)
Abstract The two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae), is a notorious pest in agriculture that has developed resistance to almost all chemical types used for its control. Here, we assembled a chromosome-level genome fo
Externí odkaz:
https://doaj.org/article/0c3d45863e884c2fbe43c0ff09ae5aa7
Autor:
Yi-Ting Wang, Yan Zhang, Chao Ma, Wei-Hua Ma, Li-Jun Cao, Jin-Cui Chen, Wei Song, Jing-Fang Yang, Xu-Yuan Gao, Hong-Song Chen, Zhen-Ya Tian, Nicolas Desneux, Shu-Jun Wei, Zhong-Shi Zhou
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-7 (2024)
Abstract The leaf beetle Ophraella communa LeSage (Coleoptera: Chrysomelidae) is an effective biological control agent of the common ragweed. Here, we assembled a chromosome-level genome of the O. communa by combining Illumina, Nanopore, and Hi-C seq
Externí odkaz:
https://doaj.org/article/5ea80780effb44b0afce14f2d225051d
Meta learning recently has been heavily researched and helped advance the contemporary machine learning. However, achieving well-performing meta-learning model requires a large amount of training tasks with high-quality meta-data representing the und
Externí odkaz:
http://arxiv.org/abs/2305.07892
Robust loss minimization is an important strategy for handling robust learning issue on noisy labels. Current approaches for designing robust losses involve the introduction of noise-robust factors, i.e., hyperparameters, to control the trade-off bet
Externí odkaz:
http://arxiv.org/abs/2301.07306
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-5 (2024)
Abstract The plum fruit moth Grapholita funebrana (Tortricidae, Lepidoptera) is an important pest of many wild and cultivated stone fruits and other plants in the family Rosaceae. Here, we assembled its nuclear and mitochondrial genomes using Illumin
Externí odkaz:
https://doaj.org/article/86e5665b39b9415c935bec331f317c5c
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-7 (2024)
Abstract The western flower thrips Frankliniella occidentalis (Thysanoptera: Thripidae) is a global invasive species that causes increasing damage by direct feeding on crops and transmission of plant viruses. Here, we assemble a previously published
Externí odkaz:
https://doaj.org/article/e9318c8d82e94e0f968d6412cad733e6