المؤلفون: Jia, Yunjian, Huang, Zhen, Yan, Jiping, Zhang, Yulu, Luo, Kun, Wen, Wanli

مصطلحات موضوعية: Computer Science - Machine Learning, Computer Science - Artificial Intelligence

الوصف: Deploying federated learning at the wireless edge introduces federated edge learning (FEEL). Given FEEL's limited communication resources and potential mislabeled data on devices, improper resource allocation or data selection can hurt convergence speed and increase training costs. Thus, to realize an efficient FEEL system, this paper emphasizes jointly optimizing resource allocation and data selection. Specifically, in this work, through rigorously modeling the training process and deriving an upper bound on FEEL's one-round convergence rate, we establish a problem of joint resource allocation and data selection, which, unfortunately, cannot be solved directly. Toward this end, we equivalently transform the original problem into a solvable form via a variable substitution and then break it into two subproblems, that is, the resource allocation problem and the data selection problem. The two subproblems are mixed-integer non-convex and integer non-convex problems, respectively, and achieving their optimal solutions is a challenging task. Based on the matching theory and applying the convex-concave procedure and gradient projection methods, we devise a low-complexity suboptimal algorithm for the two subproblems, respectively. Finally, the superiority of our proposed scheme of joint resource allocation and data selection is validated by numerical results.

الوصول الحر: http://arxiv.org/abs/2407.02888Test

المؤلفون: Luo, Kun, Liu, Zheng, Xiao, Shitao, Liu, Kang

مصطلحات موضوعية: Computer Science - Computation and Language

الوصف: Large language models (LLMs) call for extension of context to handle many critical applications. However, the existing approaches are prone to expensive costs and inferior quality of context extension. In this work, we proposeExtensible Embedding, which realizes high-quality extension of LLM's context with strong flexibility and cost-effectiveness. Extensible embedding stand as an enhancement of typical token embedding, which represents the information for an extensible scope of context instead of a single token. By leveraging such compact input units of higher information density, the LLM can access to a vast scope of context even with a small context window. Extensible embedding is systematically optimized in architecture and training method, which leads to multiple advantages. 1) High flexibility of context extension, which flexibly supports ad-hoc extension of diverse context lengths. 2) Strong sample efficiency of training, which enables the embedding model to be learned in a cost-effective way. 3) Superior compatibility with the existing LLMs, where the extensible embedding can be seamlessly introduced as a plug-in component. Comprehensive evaluations on long-context language modeling and understanding tasks verify extensible embedding as an effective, efficient, flexible, and compatible method to extend the LLM's context.

الوصول الحر: http://arxiv.org/abs/2402.11573Test

المؤلفون: Chen, Jianlv, Xiao, Shitao, Zhang, Peitian, Luo, Kun, Lian, Defu, Liu, Zheng

مصطلحات موضوعية: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning

الوصف: In this paper, we present a new embedding model, called M3-Embedding, which is distinguished for its versatility in Multi-Linguality, Multi-Functionality, and Multi-Granularity. It can support more than 100 working languages, leading to new state-of-the-art performances on multi-lingual and cross-lingual retrieval tasks. It can simultaneously perform the three common retrieval functionalities of embedding model: dense retrieval, multi-vector retrieval, and sparse retrieval, which provides a unified model foundation for real-world IR applications. It is able to process inputs of different granularities, spanning from short sentences to long documents of up to 8192 tokens. The effective training of M3-Embedding involves the following technical contributions. We propose a novel self-knowledge distillation approach, where the relevance scores from different retrieval functionalities can be integrated as the teacher signal to enhance the training quality. We also optimize the batching strategy, enabling a large batch size and high training throughput to ensure the discriminativeness of embeddings. To the best of our knowledge, M3-Embedding is the first embedding model which realizes such a strong versatility. The model and code will be publicly available at https://github.com/FlagOpen/FlagEmbeddingTest.

الوصول الحر: http://arxiv.org/abs/2402.03216Test

المؤلفون: Lin, Chung-Ching, Wang, Jiang, Luo, Kun, Lin, Kevin, Li, Linjie, Wang, Lijuan, Liu, Zicheng

مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition

الوصف: The most recent efforts in video matting have focused on eliminating trimap dependency since trimap annotations are expensive and trimap-based methods are less adaptable for real-time applications. Despite the latest tripmap-free methods showing promising results, their performance often degrades when dealing with highly diverse and unstructured videos. We address this limitation by introducing Adaptive Matting for Dynamic Videos, termed AdaM, which is a framework designed for simultaneously differentiating foregrounds from backgrounds and capturing alpha matte details of human subjects in the foreground. Two interconnected network designs are employed to achieve this goal: (1) an encoder-decoder network that produces alpha mattes and intermediate masks which are used to guide the transformer in adaptively decoding foregrounds and backgrounds, and (2) a transformer network in which long- and short-term attention combine to retain spatial and temporal contexts, facilitating the decoding of foreground details. We benchmark and study our methods on recently introduced datasets, showing that our model notably improves matting realism and temporal coherence in complex real-world videos and achieves new best-in-class generalizability. Further details and examples are available at https://github.com/microsoft/AdaMTest.
Comment: CVPR 2023

الوصول الحر: http://arxiv.org/abs/2304.06018Test

المؤلفون: Luo, Kun, Gan, Weizhuo, Hou, Zhaozhao, Zhan, Guohui, Xu, Lijun, Liu, Jiangtao, Lu, Ye, Wu, Zhenhua

مصطلحات موضوعية: Condensed Matter - Mesoscale and Nanoscale Physics

الوصف: Recently, cold source transistor (CSFET) with steep-slope subthreshold swing (SS) < 60 mV/decade has been proposed to overcome Boltzmann tyranny in its ballistic regime. However the scattering, especially by inelastic scattering may lead serious SS degradation through cold carrier thermalization. In this study, the electronic excitation/relaxation dynamic process is investigated theoretically by virtue of the state-of-the-art nonadiabatic molecular dynamics (NAMD) method, i.e., the mixed quantum-classical NAMD. The mixed quantum-classical NAMD considers both carrier decoherence and detailed balance to calculate the cold carrier thermalization and transfer processes in semiconductor Si, and metallic silicide (NiSi2 and CoSi2). The dependence of the thermalization factor, relaxation time, scattering time and scattering rate on energy level are obtained. The thermalization of carrier gradually increases from low energy to high energy. Partially thermalization from the ground state to reach the thermionic current window is realized with sub-100 $fs$ time scale. Fully thermalization to entail energy region depends on the barrier height sensitively, i.e., the scattering rate decreases exponentially as the energy of the out-scattering state increase. The scattering rate of NiSi2 and CoSi2 is 2 orders of magnitude higher than that of Si, arising from their higher density of states than that in Silicon This study can shed light on the material design for low power tunneling FET as well as the emerging CSFET.
Comment: 14 pages, 17 figres

الوصول الحر: http://arxiv.org/abs/2302.07434Test

المؤلفون: Li, Mingqiang, Shen, Yidi, Luo, Kun, An, Qi, Gao, Peng, Xiao, Penghao, Zou, Yu

المصدر: Nature Materials, 1-6 (2023)

مصطلحات موضوعية: Condensed Matter - Materials Science

الوصف: Dislocations, line defects in crystalline materials, play an essential role in the mechanical[1,2], electrical[3], optical[4], thermal[5], and phase transition[6] properties of these materials. Dislocation motion, an important mechanism underlying crystal plasticity, is critical for the hardening, processing, and application of a wide range of structural and functional materials[1,7,8]. For decades, the movement of dislocations has been widely observed in crystalline solids under mechanical loading[9-11]. However, the goal of manipulating dislocation motion via a non-mechanical field alone remains elusive. Here, we present real-time observations of dislocation motion controlled solely by an external electric field in single-crystalline zinc sulfide (ZnS). We find that 30{\deg} partial dislocations can move back and forth depending on the direction of the electric field, while 90{\deg} partial dislocations are motionless. We reveal the nonstoichiometric nature of dislocation cores using atomistic imaging and determine their charge characteristics by density functional theory calculations. The glide barriers of charged 30{\deg} partial dislocations, which are lower than those of 90{\deg} partial dislocations, further decrease under an electric field, explaining the experimental observations. This study provides direct evidence of dislocation dynamics under a non-mechanical stimulus and opens up the possibility of modulating dislocation-related properties.
Comment: https://www.nature.com/articles/s41563-023-01572-7Test

الوصول الحر: http://arxiv.org/abs/2211.14933Test

المؤلفون: Luo, Kun, Li, Baozhong, Sun, Lei, Wu, Yingju, Ge, Yanfeng, Liu, Bing, He, Julong, Xu, Bo, Zhao, Zhisheng, Tian, Yongjun

المصدر: Chin. Phys. Lett. 39, 036301 (2022)

مصطلحات موضوعية: Condensed Matter - Materials Science

الوصف: Both boron nitride (BN) and carbon (C) have sp, sp2 and sp3 hybridization modes, and thus resulting in a variety of BN and C polymorphs with similar structures, such as hexagonal BN (hBN) and graphite, cubic BN (cBN) and diamond. Here, five types of BN polymorph structures were proposed theoretically, inspired by the graphite-diamond hybrid structures discovered in recent experiment. These BN polymorphs with graphite-diamond hybrid structures possessed excellent mechanical properties with combined high hardness and high ductility, and also exhibited various electronic properties such as semi-conductivity, semi-metallicity, and even one- and two-dimensional conductivity, differing from known insulators hBN and cBN. The simulated diffraction patterns of these BN hybrid structures could account for the unsolved diffraction patterns of intermediate products composed of "compressed hBN" and diamond-like BN, caused by phase transitions in previous experiments. Thus, this work provides a theoretical basis for the presence of these types of hybrid materials during phase transitions between graphite-like and diamond-like BN polymorphs.

الوصول الحر: http://arxiv.org/abs/2112.14975Test

المؤلفون: Ge, Yanfeng, Luo, Kun, Liu, Yong, Yang, Guochun, Hu, Wentao, Li, Baozhong, Gao, Guoying, Zhou, Xiang-Feng, Xu, Bo, Zhao, Zhisheng, Tian, Yongjun

المصدر: Materials Today Physics (2022)

مصطلحات موضوعية: Condensed Matter - Materials Science

الوصف: Search for new high-temperature superconductors and insight into their superconducting mechanism are of fundamental importance in condensed matter physics. The discovery of near-room temperature superconductivity at more than a million atmospheres ushers in a new era for superconductors. However, the critical task of identifying materials with comparable superconductivity at near or ambient pressure remains. Carbon materials can always lead to intriguing surprises due to their structural diversity and electronic adjustability. Insulating diamond upon doping or external stimuli has achieved superconducting state. Thus, it still has a great opportunity to find superconducting ones with higher transition temperature (Tc). Here, we report an intrinsic superconducting graphite-diamond hybrid through first-principles calculations, whose atomic-resolution structural characteristics have been experimentally determined recently. The predicted Tc is approximated at 39 K at ambient pressure, and strain energizing can further boost Tc to 42 K. The strong electron-phonon coupling associated with the out-of-plane vibration of carbon atoms at the junction plays a dominant role in the superconducting transition. Our work demonstrates the great potential of such carbon materials as high-Tc superconductors, which will definitely attract extensive research.
Comment: 11 pages, 3 figures

الوصول الحر: http://arxiv.org/abs/2111.13863Test

المؤلفون: Liu, Jiangtao, Cai, Xun-Ming, Huang, Jin-Bao, Luo, Kun, Li, HongXu, Li, Weimin, Zhang, De-Jian, Wu, Zhenhua

مصطلحات موضوعية: Physics - Optics, Electrical Engineering and Systems Science - Image and Video Processing

الوصف: Nowadays the world has entered into the digital age, in which the data analysis and visualization have become more and more important. In analogy to imaging the real object, we demonstrate that the computational ghost imaging can image the digital data to show their characteristics, such as periodicity. Furthermore, our experimental results show that the use of optical imaging methods to analyse data exhibits unique advantages, especially in anti-interference. The data analysis with computational ghost imaging can be well performed against strong noise, random amplitude and phase changes in the binarized signals. Such robust data data analysis and imaging has an important application prospect in big data analysis, meteorology, astronomy, economics and many other fields.

الوصول الحر: http://arxiv.org/abs/2111.03790Test

المؤلفون: Qiao, Yonghui, Mao, Le, Wang, Yan, Luan, Jingyang, Chen, Yanlu, Zhu, Ting, Luo, Kun, Fan, Jianren

المصدر: Biomechanics and Modeling in Mechanobiology (2022)

مصطلحات موضوعية: Physics - Medical Physics, Physics - Fluid Dynamics

الوصف: Thoracic endovascular aortic repair (TEVAR) has become the standard treatment of a variety of aortic pathologies. The objective of this study is to evaluate the hemodynamic effects of stent-graft introducer sheath during TEVAR. Three idealized representative diseased aortas of aortic aneurysm, coarctation of the aorta, and aortic dissection were designed. Computational fluid dynamics studies were performed in the above idealized aortic geometries. An introducer sheath routinely used in the clinic was virtually-delivered into diseased aortas. Comparative analysis was carried out to evaluate the hemodynamic effects of the introducer sheath. Results show that the blood flow to the supra-aortic branches would increase above 9% due to the obstruction of the introducer sheath. The region exposed to high endothelial cell activation potential (ECAP) expands in the scenarios of coarctation of the aorta and aortic dissection, which indicates that the probability of thrombus formation may increase during TEVAR. The pressure magnitude in peak systole shows an obvious rise and a similar phenomenon is not observed in early diastole. The blood viscosity in the aortic arch and descending aorta is remarkably altered by the introducer sheath. The uneven viscosity distribution confirms the necessity of using non-Newtonian models and high viscosity region with high ECAP further promotes thrombosis. Our results highlight the hemodynamic effects of stent-graft introducer sheath during TEVAR, which may associate with perioperative complications.

الوصول الحر: http://arxiv.org/abs/2107.04407Test