Zobrazeno 1 - 10
of 9 017
pro vyhledávání: '"Xiao-rong AN"'
Autor:
Wei, Guoting, Yuan, Xia, Liu, Yu, Shang, Zhenhao, Yao, Kelu, Li, Chao, Yan, Qingsen, Zhao, Chunxia, Zhang, Haokui, Xiao, Rong
Aerial object detection has been a hot topic for many years due to its wide application requirements. However, most existing approaches can only handle predefined categories, which limits their applicability for the open scenarios in real-world. In t
Externí odkaz:
http://arxiv.org/abs/2408.12246
The Bell nonlocality and entanglement are two kinds of quantum correlations in quantum systems. Due to the recent upgrade in Beijing Spectrometer III (BESIII) experiment, it is possible to explore the nonlocality and entanglement in hyperon-antihyper
Externí odkaz:
http://arxiv.org/abs/2406.16298
Leveraging generative retrieval (GR) techniques to enhance search systems is an emerging methodology that has shown promising results in recent years. In GR, a text-to-text model maps string queries directly to relevant document identifiers (docIDs),
Externí odkaz:
http://arxiv.org/abs/2404.15675
Autor:
Xiao, Rong, Zhao, Y. X.
Publikováno v:
Nat Commun 15, 3787 (2024)
The sublattice symmetry on a bipartite lattice is commonly regarded as the chiral symmetry in the AIII class of the tenfold Altland-Zirnbauer classification. Here, we reveal the spatial nature of sublattice symmetry, and show that this assertion hold
Externí odkaz:
http://arxiv.org/abs/2404.11398
Publikováno v:
Chin. Phys. C 48, 084104 (2024)
A correlation between the charge radii difference of mirror partner nuclei $\Delta{R_{\mathrm{ch}}}$ and the slope parameter $L$ of symmetry energy has been built to ascertain the equation of state of isospin asymmetric nuclear matter. In this work,
Externí odkaz:
http://arxiv.org/abs/2404.08982
This research aims to accelerate the inference speed of large language models (LLMs) with billions of parameters. We propose \textbf{S}mart \textbf{P}arallel \textbf{A}uto-\textbf{C}orrect d\textbf{E}coding (SPACE), an innovative approach designed fo
Externí odkaz:
http://arxiv.org/abs/2402.11809
Large language models (LLMs) commonly employ autoregressive generation during inference, leading to high memory bandwidth demand and consequently extended latency. To mitigate this inefficiency, we present Bi-directional Tuning for lossless Accelerat
Externí odkaz:
http://arxiv.org/abs/2401.12522
Data-driven deep learning methods have shown great potential in cropland mapping. However, due to multiple factors such as attributes of cropland (topography, climate, crop type) and imaging conditions (viewing angle, illumination, scale), croplands
Externí odkaz:
http://arxiv.org/abs/2310.10219
Autor:
Li-li QIAN, De-zun MA, Peng-fei GAO, Sheng-wang JIANG, Qing-qing WANG, Chun-bo CAI, Gao-jun XIAO, Xiao-rong AN, Wen-tao CUI
Publikováno v:
Journal of Integrative Agriculture, Vol 15, Iss 11, Pp 2571-2577 (2016)
Myostatin, a member of the transforming growth factor beta (TGF-β) superfamily, is a dominant inhibitor that acts to limit skeletal muscle growth and development. In this study, we generated transgenic mice that express porcine myostatin containg mu
Externí odkaz:
https://doaj.org/article/688fedac46944903bfab4a9bf7930d56
Autor:
Liang, Yu, Zhang, Yufeng, Zhang, Shiliang, Wang, Yaowei, Xiao, Sheng, Xiao, Rong, Wang, Xiaoyu
Backward-compatible training circumvents the need for expensive updates to the old gallery database when deploying an advanced new model in the retrieval system. Previous methods achieved backward compatibility by aligning prototypes of the new model
Externí odkaz:
http://arxiv.org/abs/2308.06948