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arXiv 2024年

作者： Gao, Bofei Song, Feifan Yang, Zhe Cai, Zefan Miao, Yibo Dong, Qingxiu Li, Lei Ma, Chenghao Chen, Liang Xu, Runxin Tang, Zhengyang Wang, Benyou Zan, Daoguang Quan, Shanghaoran Zhang, Ge Sha, Lei Zhang, Yichang Ren, Xuancheng Liu, Tianyu Chang, Baobao Peking University China University of Wisconsin - Madison United States Alibaba Group China Shanghai Jiao Tong University China Engineering Research Center of Information Networks The Chinese University of Hong Kong Shenzhen China Institute of Software Chinese Academy of Sciences China University of Waterloo Canada The University of Hong Kong Hong Kong Zhongguancun Laboratory China

Recent advancements in large language models (LLMs) have led to significant breakthroughs in mathematical reasoning capabilities. However, existing benchmarks like GSM8K or MATH are now being solved with high accuracy (e.g., OpenAI o1 achieves 94.8% on MATH dataset), indicating their inadequacy for truly challenging these models. To bridge this gap, we propose a comprehensive and challenging benchmark specifically designed to assess LLMs’ mathematical reasoning at the Olympiad level. Unlike existing Olympiad-related benchmarks, our dataset focuses exclusively on mathematics and comprises a vast collection of 4428 competition-level problems with rigorous human annotation. These problems are meticulously categorized into over 33 sub-domains and span more than 10 distinct difficulty levels, enabling a holistic assessment of model performance in Olympiad-mathematical reasoning. Furthermore, we conducted an in-depth analysis based on this benchmark. Our experimental results show that even the most advanced models, OpenAI o1-mini and OpenAI o1-preview, struggle with highly challenging Olympiad-level problems, with 60.54% and 52.55% accuracy, highlighting significant challenges in Olympiad-level mathematical reasoning. © 2024, CC0.

关键词： Benchmarking

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Data security and privacy computing in artificial intelligence

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Journal of Information and Intelligence 2024年第2期2卷 99-101页

作者： Dengguo Feng Hui Li Rongxing Lu Zheli Liu Jianbing Ni Hui Zhu Institute of Software Academy of SciencesBeijing 100190China State Key Laboratory of Integrated Services Networks School of Cyber EngineeringXidian UniversityXi’an 710071China Faculty of Computer Science University of New BrunswickFredericton E3B 5A3Canada College of Computer Science Nankai UniversityTianjin 300071China Department of Electrical and Computer Engineering Queen’s UniversityKingston K7L 3N6Canada

Artificial intelligence(AI)is a field of computer science dedicated to creating systems and algorithms that can perform tasks typically requiring human intelligence,such as learning,problem-solving,language understanding,and decision-making,contributing to a wide array of applications across diverse *** development of AI,such as machine learning and deep learning,has revolutionized data processing and *** transformation is rapidly changing human life and has allowed for many practical AI based applications,including biometric recognition,text/sentimental analysis,and attack detection in the fields of health care,finance,autonomous vehicles,personalized ***,the potential benefits of AI are hindered by issues,such as insecurity and privacy violations in data processing and communication.

关键词： such has finance

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Machine Unlearning: Taxonomy, Metrics, Applications, Challenges, and Prospects

arXiv

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arXiv 2024年

作者： Li, Na Zhou, Chunyi Gao, Yansong Chen, Hui Fu, Anmin Zhang, Zhi Yu, Shui School of Cyberspace Science and Engineering Nanjing University of Science and Technology Nanjing210094 China State Key Laboratory of Integrated Services Networks Xidian University Xi’an710071 China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Data61 CSIRO CanberraACT2601 Australia Department of Computer Science and Software Engineering University of Western Australia PerthWA6009 Australia School of Computer Science University of Technology Sydney SydneyNSW2007 Australia

Personal digital data is a critical asset, and governments worldwide have enforced laws and regulations to protect data privacy. Data users have been endowed with the 'right to be forgotten' of their data. In the course of machine learning (ML), the forgotten right requires a model provider to delete user data and its subsequent impact on ML models upon user requests. Machine unlearning emerges to address this, which has garnered ever-increasing attention from both industry and academia. While the area has developed rapidly, there is a lack of comprehensive surveys to capture the latest advancements. Recognizing this shortage, we conduct an extensive exploration to map the landscape of machine unlearning including the (fine-grained) taxonomy of unlearning algorithms under centralized and distributed settings, debate on approximate unlearning, verification and evaluation metrics, challenges and solutions for unlearning under different applications, as well as attacks targeting machine unlearning. The survey concludes by outlining potential directions for future research, hoping to serve as a guide for interested scholars. Copyright © 2024, The Authors. All rights reserved.

关键词： Taxonomies

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Where to Start: Studying Type Annotation Practices in Python 21

Where to Start: Studying Type Annotation Practices in Python

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IEEE International Conference on Automated software engineering (ASE)

作者： Wuxia Jin Dinghong Zhong Zifan Ding Ming Fan Ting Liu School of Software Engineering Xi’an Jiaotong University Xi’an China Ministry of Education Key Laboratory of Intelligent Networks and Network Security Xi’an Jiaotong University

ISBN: (纸本)9781665447843

Dynamic programming languages have been embracing gradual typing, which supports optional type annotations in source code. Type-annotating a complex and long-lasting codebase is indeed a gradual and expensive process, where two issues have troubled developers. First, there is few guidance about how to implement type annotations due to the existence of non-trivial type practices; second, there is few guidance about which portion of a codebase should be type-annotated first. To address these issues, this paper investigates the patterns of non-trivial type-annotation practices and features of type-annotated code files. Our study detected six patterns of type-annotation practices, which involve recovering and expressing design concerns. Moreover, we revealed three complementary features of type-annotated files. Besides, we implemented a tool for studying optional typing practice. We suggest that: 1) design concerns should be considered to improve type annotation implementation by following at least six patterns; 2) files critical to software architecture could be type-annotated in priority. We believe these guidelines would promote a better type annotation practice for dynamic languages.

关键词： Codes Costs Annotations software architecture Maintenance engineering Feature extraction Dynamic programming

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Analysis of the Spectral Efficiency of a MIMO-NOMA System with Spatial Multiplexing

Analysis of the Spectral Efficiency of a MIMO-NOMA System wi...

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Wave Electronics and its Application in Information and Telecommunication Systems (WECONF)

作者： Ilya Grishin Grigoriy Fokin Alla Kalinkina Alexander Sinilnikov Vladimir Sevidov Department of Communication Networks and Data Transmission The Bonch-Bruevich Saint Petersburg State University of Telecommunications Saint Petersburg Russia Software Defined Radio Laboratory The Bonch-Bruevich Saint Petersburg State University of Telecommunications Saint Petersburg Russia Center for Satellite Communication Leningrad Branch of the FSBI NIIR Saint Petersburg Russia Department of Radio Engineering S.M. Budyonny VAS Saint Petersburg Russia

ISBN: (数字)9781665465687

ISBN: (纸本)9781665465694

This study analyzes the spectral efficiency of MIMO-NOMA systems combining spatial multiplexing, correlation-based user clustering, and power allocation by the Lagrange multipliers method. These methods are selected to minimize interference and maximize downlink throughput. Simulations demonstrate the configuration’s effectiveness in high-mobility and partial-coverage scenarios.

关键词： Spectral efficiency Heuristic algorithms Precoding Clustering algorithms Interference Throughput MIMO Telecommunications Space division multiplexing Resource management

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An Efficient Searchable Encryption Framework with Weighted Keywords for the Internet of Medical Things (IoMT)

TechRxiv

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TechRxiv 2022年

作者： Wang, Haiyan Li, Yuan He, Ying Luo, Fucai Yu, F. Richard Ming, Zhong Wang, Shulan The College of Computer Science and Software Engineering Shenzhen University Shenzhen China The Department of New Networks Pengcheng Laboratory Shenzhen China The Department of Systems and Computer Engineer Carleton University OttawaON Canada The College of Big Data and Internet Shenzhen Technology University Shenzhen China

With the increasing popularity of smart terminals, the Internet of Things (IoT) vastly expands the influence of information technology and creates great values to our society. The Internet of Medical Things (IoMT) is a typical application of the IoT specifically for medical and healthcare related purposes. In IoMT, personal health records (PHRs) generated by intelligent equipment are usually stored in a cloud sever managed by a semi-trusted cloud provider. However, there is still a possibility of the exposure of private information to unauthorized parties. In order to protect a patient’s private information, and ensure that doctors can search a patient’s PHRs without decrypting all ciphertexts, an efficient searchable encryption framework with weighted keywords is proposed in this paper. In this framework, we implement a weighted keyword model to raise the accuracy of search results, and reduce the computational and storage overhead. Besides, compared with the existing schemes, the framework is supportable of multi-search mechanism, which is adaptable to more application scenarios. Finally, the efficiency and security of this framework is proved through security and performance analysis in this paper. © 2022, CC BY.

关键词： Cryptography

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Auction Theory and Game Theory Based Pricing of Edge Computing Resources: A Survey

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IEEE Internet of Things Journal 2025年

作者： Yu, Jiguo Liu, Shun Zou, Yifei Wang, Guijuan Hu, Chunqiang University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu610054 China Qilu University of Technology Big Data Institute Jinan250353 China Qufu Normal University School of Computer Science Shandong Rizhao China Shandong University School of Computer Science and Technology Shandong Qingdao266237 China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan250353 China Chongqing University School of Big Data and Software Engineering Chongqing400044 China

The proliferation of Internet of Things (IoT) devices and edge computing applications has heightened the demand for efficient resource allocation and pricing mechanisms. Effective pricing strategies play a crucial role in optimizing resource utilization, reducing latency, and ensuring fair resource distribution among users. Both auction theory and game theory have emerged as fundamental economic frameworks for designing pricing mechanisms in edge computing. This paper presents a comprehensive survey of pricing strategies that leverage both auction and game theory, systematically categorizing existing research based on auction mechanisms and game-theoretic models. Unlike previous surveys that focus solely on auction-based pricing, this work integrates game-theoretic perspectives, providing a holistic analysis of strategic interactions in edge computing resource allocation. Furthermore, we discuss key challenges, emerging trends, and future research directions aimed at enhancing efficiency, fairness, and privacy protection in cloud-edge collaborative computing environments. © 2014 IEEE.

关键词： Mobile edge computing

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2.5D Optoelectronic Integration for 400G (8×56Gbps) CPO-based Optical Interconnects

2.5D Optoelectronic Integration for 400G (8×56Gbps) CPO-bas...

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2021 Asia Communications and Photonics Conference, ACP 2021

作者： Yang, Xuecheng Du, Jiangbing Liu, Jiacheng Wang, Xinyi Tang, Ningfeng Shang, Yingchun He, Zuyuan State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China ZTE Corp. 50 Software Avenue YuHuaTai District Nanjing210012 China ZTE Corp. 6 Huashiyuan Rd Donghu H.D.Z. Wuhan430223 China

A proof-of-concept 2.5D optoelectronic integration solution for CPO applications is demonstrated, based on organic substrate, silicon photonics, flip-chip. Pre-FEC BER under 0.02 is obtained for 56Gbps OOK signals, in... 详细信息

ISBN: (纸本)9781957171005

关键词： Silicon photonics

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Resource Optimization for LEO Constellation networks: A Multi-satellite Cooperative Coverage Design

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IEEE Transactions on Communications 2025年

作者： Ma, Xu Zhang, Haijun Song, Wei Lu, Yang Wu, Yuan Leung, Victor C.M University of Science and Technology Beijing Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services Beijing100083 China China Electric Power Research Institute Co. Ltd Beijing102209 China University of Macau State Key Laboratory of Internet of Things for Smart City Macau China University of Macau Department of Computer and Information Science Macau China Shenzhen University Department of Computer Science and Software Engineering Shenzhen518061 China

With its low latency, high throughput, good deployment flexibility, and cost-effectiveness, the low earth orbit (LEO) constellation is regarded as a promising technology for seamless coverage. Unlike geosynchronous orbiting (GSO) satellites, the highly dynamic evolution of LEO constellation topology poses a significant challenge to the traditional scheme of allocating wireless resources. This paper proposes a multisatellite cooperative coverage resource allocation for the LEO constellation. A multi-objective optimization problem focusing on throughput and coverage time is proposed for the overall service quality of the LEO constellation. To solve the complex coupling between multi-domain resources, the optimization problem is decomposed into three key subproblems, which are the beam placement problem, the joint beam association with power allocation problem, and the beam hopping time slot allocation problem. For each subproblem, an adaptive algorithm is proposed that effectively exploits the payload of LEO satellites to ensure the coverage performance of the constellation network. Simulation results demonstrate that the proposed coverage scheme enables fast convergence, enhances network throughput utility, and guarantees the stability and fairness of the communication services. © 1972-2012 IEEE.

关键词： Multiobjective optimization

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A Low Self-Noise Fiber Optic Gyroscope Based on Dual-polarization Configuration for Geophysical Rotation Sensing

A Low Self-Noise Fiber Optic Gyroscope Based on Dual-polariz...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Yanjun Chen Yuwen Cao Wenbo Wang Yan He Tong Zhou Zhengbin Lil State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China School of Software and Microelectronics Peking University Beijing China

A fiber optic gyroscope based on dual-polarization configuration is designed and realized. The 24-hour stability test shows aself-noise level of $3\times 10^{-9}$ rad $/\mathrm{s}/\surd{\text{Hz}}$ within the freq... 详细信息

ISBN: (纸本)9781957171005

关键词： Vibrations Sensitivity Earthquakes Asia Frequency response Gyroscopes Sensors

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