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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Lee, Gihun Jeong, Minchan Kim, Yujin Jung, Hojung Oh, Jaehoon Kim, Sangmook Yun, Se-Young Graduate School of AI KAIST Korea Republic of Samsung Advanced Institute of Technology Korea Republic of Department of Electrical and Computer Engineering UBC Canada

ISBN: (纸本)9798891761681

While learning to align Large Language Models (LLMs) with human preferences has shown remarkable success, aligning these models to meet the diverse user preferences presents further challenges in preserving previous knowledge. This paper examines the impact of personalized preference optimization on LLMs, revealing that the extent of knowledge loss varies significantly with preference heterogeneity. Although previous approaches have utilized the KL constraint between the reference model and the policy model, we observe that they fail to maintain global knowledge and general alignment when facing personalized preferences. To this end, we introduce Base-Anchored Preference Optimization (BAPO), a simple yet effective approach that utilizes the initial responses of reference model to mitigate forgetting while accommodating personalized alignment. BAPO effectively adapts to diverse user preferences while minimally affecting global knowledge or general alignment. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Dual-logic-in-memory implementation with orthogonal polarization of van der Waals ferroelectric heterostructure

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InfoMat 2024年第2期6卷 107-117页

作者： Jingjie Niu Sumin Jeon Donggyu Kim Sungpyo Baek Hyun Ho Yoo Jie Li Ji-Sang Park Yoonmyung Lee Sungjoo Lee SKKU Advanced Institute of Nanotechnology(SAINT) Sungkyunkwan UniversitySuwonRepublic of Korea Department of Nano Science and Technology Sungkyunkwan UniversitySuwonRepublic of Korea Department of Electrical and Computer Engineering Sungkyunkwan UniversitySuwonRepublic of Korea IMEC HeverleeBelgium Department of Nano Engineering Sungkyunkwan UniversitySuwonRepublic of Korea

The rapid advancement of AI-enabled applications has resulted in an increasing need for energy-efficient computing ***-in-memory is a promising approach for processing the data stored in memory,wherein fast and efficient computations are possible owing to the parallel execution of reconfigurable logic *** this study,a dual-logic-in-memory device,which can simultaneously perform two logic operations in four states,is demonstrated using van der Waals ferroelectric field-effect transistors(vdW FeFETs).The proposed dual-logic-in-memory device,which also acts as a twobit storage device,is a single bidirectional polarization-integrated ferroelectric field-effect transistor(BPI-FeFET).It is fabricated by integrating an in-plane vdW ferroelectric semiconductor SnS and an out-of-plane vdW ferroelectric gate dielectric material—CuInP_(2)S_(6).Four reliable resistance states with excellent endurance and retention characteristics were *** two-bit storage mechanism in a BPI-FeFET was analyzed from two perspectives:carrier density and carrier injection controls,which originated from the out-of-plane polarization of the gate dielectric and in-plane polarization of the semiconductor,*** conventional multilevel FeFETs,the proposed BPIFeFET does not require additional pre-examination or erasing steps to switch from/to an intermediate polarization,enabling direct switching between the four memory *** utilize the fabricated BPI-FeFET as a dual-logic-inmemory device,two logical operations were selected(XOR and AND),and their parallel execution was *** types of logic operations could be implemented by selecting different initial states,demonstrating various types of functions required for numerous neural network *** flexibility and efficiency of the proposed dual-logic-in-memory device appear promising in the realization of next-generation low-power computing systems.

关键词： ferroelectric field-effect transistor in-plane ferroelectricity logic-in-memory out-of-plane ferroelectricity

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A deep Q-learning model for sequential task offloading in edge AI systems

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Intelligent and Converged Networks 2024年第3期5卷 207-221页

作者： Dong Liu Shiheng Gu Xinyu Fan Xu Zheng Department of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu 610000China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen 515100China Department of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610000China

Currently,edge Artificial Intelligence(AI)systems have significantly facilitated the functionalities of intelligent devices such as smartphones and smart cars,and supported diverse applications and *** fundamental supports come from continuous data analysis and computation over these *** the resource constraints of terminal devices,multi-layer edge artificial intelligence systems improve the overall computing power of the system by scheduling computing tasks to edge and cloud servers for *** efforts tend to ignore the nature of strong pipelined characteristics of processing tasks in edge AI systems,such as the encryption,decryption and consensus algorithm supporting the implementation of Blockchain ***,this paper proposes a new pipelined task scheduling algorithm(referred to as PTS-RDQN),which utilizes the system representation ability of deep reinforcement learning and integrates multiple dimensional information to achieve global task ***,a co-optimization strategy based on Rainbow Deep Q-Learning(RainbowDQN)is proposed to allocate computation tasks for mobile devices,edge and cloud servers,which is able to comprehensively consider the balance of task turnaround time,link quality,and other factors,thus effectively improving system performance and user *** addition,a task scheduling strategy based on PTS-RDQN is proposed,which is capable of realizing dynamic task allocation according to device *** results based on many simulation experiments show that the proposed method can effectively improve the resource utilization,and provide an effective task scheduling strategy for the edge computing system with cloud-edge-end architecture.

关键词： edge computing task scheduling reinforcement learning Rainbow Deep Q-Learning(RainbowDQN)

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Real-Time Digital RF Emulation - Part I: The Direct Path Computational Model

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2024年 2卷 866-879页

作者： DeLude, C. Driscoll, J. Mukherjee, M. Rahman, N. Mao, X. Kamal, U. Khan, S. Sivaraman, H. Huang, E. Mcharg, J. Swaminathan, M. Pande, S. Mukhopadhyay, S. Romberg, J. Georgia Institute of Technology School of Computer Science AtlantaGA30332 United States MIT Lincoln Laboratory Advanced Concepts and Technologies Group LexingtonMA02421 United States Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA30332 United States Department of Electrical Engineering State CollegePA16802 United States

In this article, we consider the problem of developing a computational model for emulating an RF channel. The motivation for this is that an accurate and scalable emulator has the potential to minimize the need for field testing, which is expensive, slow, and difficult to replicate. Traditionally, emulators are built using a tapped delay line (TDL) model where long filters modeling the physical interactions of objects are implemented directly. For an emulation scenario consisting of M objects all interacting with one another, the TDL model's computational requirements scale as O(M3) per sample: there are O(M2) channels, each with O(M) complexity. In this article, we develop a new "direct path"model that, while remaining physically faithful, allows us to carefully factor the emulator operations, resulting in an O(M2) per-sample scaling of the computational requirements. The impact of this is drastic, a 200-object scenario sees about a 100× reduction in the number of per-sample computations. Furthermore, the direct path model gives us a natural way to distribute the computations for an emulation: each object is mapped to a computational node, and these nodes are networked in a fully connected communication graph. Alongside a discussion of the model and the physical phenomena it emulates, we show how to efficiently parameterize antenna responses and scattering profiles within this direct path framework. To verify the model and demonstrate its viability in hardware, we provide several numerical experiments produced using a cycle-level C++ simulator of a hardware implementation of the model. © 2023 IEEE.

关键词： C++ (programming language)

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Adaptive Fine-Grained Feature Mining and RoI Feature Interaction Network for Small Object Detection in Aerial Images

Adaptive Fine-Grained Feature Mining and RoI Feature Interac...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Xie, Fangmin Xiong, Zhan Wang, Zhuoyue Yang, Kun Xiao, Guoqiang College of Computer and Information Science Southwest University Chongqing China Institute of Advanced Computer Science Leiden University Netherlands Department of Electrical Engineering and Computer Sciences University of California Berkeley Berkeley United States

ISBN: (纸本)9798350368741

Object detection in drone view images remains challenging due to small-scale objects distributed non-uniformly and exhibiting weak semantic features. Additionally, external factors such as lighting conditions, viewing angles, and background clutter further complicate the detection of small objects. To address these issues, we propose a small object detector called Adaptive Fine-grained Feature Mining Network (AFMNet) based on an anchor-free framework. Firstly, an Adaptive Fine-grained Feature Mining (AFFM) module is designed to generate Regions of Interest (RoI) on high-resolution feature maps and mine fine-grained information that benefits the representation of small objects. Secondly, an Inter-RoI Feature Interaction (IRFI) block is developed to efficiently integrate complementary cues-namely, deep layer semantic information and shallow layer spatial details-and enhance RoI features. Experiments on the VisDrone dataset demonstrate that our method achieves state-of-the-art performance. The source code of our AFMNet is available at https://***/xiefangmin/AFMNet. © 2025 IEEE.

关键词： Drone-View Image Feature Fusion Fine-grained Features Region of Interest Small object detection

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Elite-guided equilibrium optimiser based on information enhancement:Algorithm and mobile edge computing applications

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CAAI Transactions on Intelligence Technology 2024年第5期9卷 1126-1171页

作者： Zong-Shan Wang Shi-Jin Li Hong-Wei Ding Gaurav Dhiman Peng Hou Ai-Shan Li Peng Hu Zhi-Jun Yang Jie Wang School of Information Science and Engineering Yunnan UniversityKunmingChina Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhenChina Academic Affairs Office Yunnan University of Finance and EconomicsKunmingChina Faculty of Management and Economics Kunming University of TechnologyKunmingChina Department of Electrical and Computer Engineering Lebanese American UniversityBeirutLebanon Department of Computer Science and Engineering University Centre for Research and DevelopmentChandigarh UniversityChennaiIndia Department of Computer Science and Engineering Graphic Era Deemed to Be UniversityDehradunIndia School of Computer Science Fudan UniversityShanghaiChina Rackham Graduate School University of MichiganAnn ArborMIUSA Research and Development Department Youbei Technology Co.LTDKunmingChina School of Mechanical and Power Engineering Zhengzhou UniversityZhengzhouChina

The Equilibrium Optimiser(EO)has been demonstrated to be one of the metaheuristic algorithms that can effectively solve global optimisation *** the paradox between exploration and exploitation operations while enhancing the ability to jump out of the local optimum are two key points to be addressed in EO *** alleviate these limitations,an EO variant named adaptive elite-guided Equilibrium Optimiser(AEEO)is ***,the adaptive elite-guided search mechanism enhances the balance between exploration and *** modified mutualism phase reinforces the information interaction among particles and local optima *** cooperation of these two mechanisms boosts the overall performance of the basic *** AEEO is subjected to competitive experiments with state-of-the-art algorithms and modified algorithms on 23 classical benchmark functions and IEE CEC 2017 function test *** results demonstrate that AEEO outperforms several well-performing EO variants,DE variants,PSO variants,SSA variants,and GWO variants in terms of convergence speed and *** addition,the AEEO algorithm is used for the edge server(ES)placement problem in mobile edge computing(MEC)*** experimental results show that the author’s approach outperforms the representative approaches compared in terms of access latency and deployment cost.

关键词： ANT COLONY optimization CLOUD COMPUTING GENETIC ALGORITHMS SWARM intelligence

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A Reconfigurable Intelligent Surface for Arbitrary mm-Wave Polarization Using Parasitic Enhancing Structures

A Reconfigurable Intelligent Surface for Arbitrary mm-Wave P...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Rao, Junhui Zhang, Yujie Murch, Ross Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Institute for Advanced Study Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong

ISBN: (纸本)9781665442282

The design of a reconfigurable intelligent surface (RIS) for mm-waves with arbitrary polarization is proposed. At mm-wave frequencies, the RF switches needed in the RIS suffer from low isolation, and therefore a parasitic enhancing structure (PES) is also proposed to improve switch performance. In the RIS element, a dual-port dual-polarized patch antenna is used for scattering. Both ports of the antenna are connected to independent phase-reconfigurable circuits based on diodes, with PES, and these can provide 180-degree phase shifts. Simulation results show that the RIS can operate effectively for two orthogonal polarized waves and therefore an arbitrarily polarized wave. © 2023 IEEE.

关键词： Microstrip antennas

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New EVENODD+ Codes with More Flexible Parameters and Lower Complexity

New EVENODD+ Codes with More Flexible Parameters and Lower C...

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2024 IEEE International Symposium on Information Theory, ISIT 2024

作者： Zhu, Panyu Lv, Jingjie Han, Yunghsiang S. Song, Linqi Hou, Hanxu School of Electrical Engineering & Intelligentization Dongguan University of Technology China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China China City University of Hong Kong Department of Computer Science Hong Kong

ISBN: (纸本)9798350382846

EVENODD+ codes are binary maximum distance separable (MDS) array codes for correcting double disk failures in RAID-6 with asymptotically optimal encoding/decoding/update complexities. However, the number of bits stored in each disk of EVENODD+ codes should be an odd number minus one. In this paper, we present a new construction of EVENODD+ codes that have more flexible parameters. The number of bits stored in each disk of our codes is an odd minus one times any positive integer. Moreover, our codes not only have asymptotically optimal encoding/decoding/update complexities but also have lower encoding/decoding/update complexities than the existing EVENODD+ codes. © 2024 IEEE.

关键词： Encoding (symbols)

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Unpaired remote sensing image super-resolution with content-preserving weak supervision neural network

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Science China(Information Sciences) 2023年第1期66卷 324-325页

作者： Jie WU Runmin CONG Leyuan FANG Chunle GUO Bob ZHANG Pedram GHAMISI College of Electrical and Information Engineering Hunan University Institute of Information Science Beijing Jiaotong University College of Computer Science Nankai University Department of Computer and Information Science University of Macau Helmholtz-Zentrum Dresden-Rossendorf Helmholtz Institute Freiberg for Resource Technology Institute of Advanced Research in Artificial Intelligence (IARAI)

Dear editor,Image super-resolution(SR) uses image processing methods to increase the resolution of the image without increasing any hardware cost. Remote sensing images with high spatial resolution contain rich imagery information, which can be utilized for object detection, building segmentation, building extraction, change detection, and so on.

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Ultrasonic-based Passenger Boarding Determination System for Trams

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Journal of institute of Control, Robotics and Systems 2023年第4期29卷 308-313页

作者： Lee, Seung-Cheol Kwak, Jae-Ho Hwang, Hyeon-Chyeol Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of Advanced Railroad Vehicle Division Korea Railroad Research Institute Korea Republic of Smart Tram Research Department Korea Railroad Research Institute Korea Republic of

In this paper, a system that can determine whether a passenger is on the tram by using only the ultrasonic generator inside the tram vehicle and the built-in microphone of the smartphone was proposed. Due to the probabilistic uncertainty of radio waves, determining whether a passenger is on the tram by using existing local wireless communication methods (e.g., WI-FI and BLE) is difficult when a passenger is near the boundary between the interior and exterior of the vehicle. To overcome this problem, in this study, ultrasonic signal, which has excellent shielding property between obstacles or barriers, was used to determine the interior or exterior of the vehicle. The door of the vehicle is closed, and the indoor ultrasonic generator emits ultrasonic waves of a specific frequency only under certain driving conditions. We developed a smartphone app based on the discrete Fourier transform algorithm to determine whether a passenger is on the tram. We installed the system on a tram of the Osong Tram Test Line and evaluated its effectiveness. © ICROS 2023.

关键词： Smartphones

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