{"list":"other","total":226,"rows":[{"id":"2305.15021","title":"EmbodiedGPT: Vision-Language Pre-Training via Embodied Chain of Thought","created":"2023-05-24","cited_by_count":279},{"id":"2110.01167","title":"Trustworthy AI: From Principles to Practices","created":"2021-10-04","cited_by_count":207},{"id":"2111.08834","title":"Federated Learning for Smart Healthcare: A Survey","created":"2021-11-16","cited_by_count":184},{"id":"2407.18921","title":"Mobile Edge Intelligence for Large Language Models: A Contemporary Survey","created":"2024-07-09","cited_by_count":128},{"id":"1907.08349","title":"Convergence of Edge Computing and Deep Learning: A Comprehensive Survey","created":"2019-07-19","cited_by_count":120},{"id":"2110.12894","title":"The Efficiency Misnomer","created":"2021-10-25","cited_by_count":98},{"id":"2111.12444","title":"Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications","created":"2021-11-24","cited_by_count":97},{"id":"2002.09668","title":"Communication-Efficient Edge AI: Algorithms and Systems","created":"2020-02-22","cited_by_count":96},{"id":"2303.15991","title":"Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks","created":"2023-03-26","cited_by_count":95},{"id":"2309.16739","title":"Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities","created":"2023-09-28","cited_by_count":90},{"id":"2303.16129","title":"Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services","created":"2023-03-28","cited_by_count":76},{"id":"2308.14352","title":"EdgeMoE: Empowering Sparse Large Language Models on Mobile Devices","created":"2023-08-28","cited_by_count":69},{"id":"2306.12194","title":"Split Learning in 6G Edge Networks","created":"2023-06-21","cited_by_count":68},{"id":"2012.03257","title":"CoEdge: Cooperative DNN Inference with Adaptive Workload Partitioning over Heterogeneous Edge Devices","created":"2020-12-06","cited_by_count":67},{"id":"2003.13376","title":"End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things","created":"2020-03-30","cited_by_count":64},{"id":"2002.10671","title":"Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework","created":"2020-02-25","cited_by_count":59},{"id":"2101.07511","title":"Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge","created":"2021-01-19","cited_by_count":56},{"id":"2007.07122","title":"Energy-Efficient Resource Management for Federated Edge Learning with CPU-GPU Heterogeneous Computing","created":"2020-07-14","cited_by_count":39},{"id":"2111.06061","title":"Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI","created":"2021-11-11","cited_by_count":39},{"id":"2201.11248","title":"Electrical Load Forecasting Using Edge Computing and Federated Learning","created":"2022-01-27","cited_by_count":34},{"id":"2102.05188","title":"CaPC Learning: Confidential and Private Collaborative Learning","created":"2021-02-09","cited_by_count":33},{"id":"2312.05693","title":"Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge","created":"2023-12-09","cited_by_count":33},{"id":"1905.13577","title":"Efficient Neural Architecture Search via Proximal Iterations","created":"2019-05-30","cited_by_count":31},{"id":"2108.13041","title":"Auto-Split: A General Framework of Collaborative Edge-Cloud AI","created":"2021-08-30","cited_by_count":30},{"id":"1906.02287","title":"Automated Machine Learning: State-of-The-Art and Open Challenges","created":"2019-06-05","cited_by_count":29},{"id":"2006.14284","title":"Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation","created":"2020-06-25","cited_by_count":27},{"id":"2112.06872","title":"Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors","created":"2021-12-13","cited_by_count":25},{"id":"2302.07335","title":"Intelligent Model Update Strategy for Sequential Recommendation","created":"2023-02-14","cited_by_count":25},{"id":"2312.00333","title":"Green Edge AI: A Contemporary Survey","created":"2023-12-01","cited_by_count":25},{"id":"2008.01916","title":"More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence","created":"2020-08-05","cited_by_count":23},{"id":"2205.14942","title":"Edge YOLO: Real-Time Intelligent Object Detection System Based on Edge-Cloud Cooperation in Autonomous Vehicles","created":"2022-05-30","cited_by_count":22},{"id":"1805.08932","title":"Large-Scale Neuromorphic Spiking Array Processors: A quest to mimic the brain","created":"2018-05-23","cited_by_count":21},{"id":"1907.07212","title":"Helen: Maliciously Secure Coopetitive Learning for Linear Models","created":"2019-07-16","cited_by_count":21},{"id":"2202.01971","title":"Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization","created":"2022-02-04","cited_by_count":19},{"id":"2303.07129","title":"AdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environments","created":"2023-03-13","cited_by_count":19},{"id":"1911.02794","title":"A Survey on Edge Computing Systems and Tools","created":"2019-11-07","cited_by_count":17},{"id":"2009.12430","title":"Pareto-Optimal Bit Allocation for Collaborative Intelligence","created":"2020-09-25","cited_by_count":17},{"id":"2105.04104","title":"AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference","created":"2021-05-10","cited_by_count":17},{"id":"2108.08059","title":"Resource Scheduling in Edge Computing: A Survey","created":"2021-08-18","cited_by_count":17},{"id":"1912.07902","title":"Asynchronous Federated Learning with Differential Privacy for Edge Intelligence","created":"2019-12-17","cited_by_count":16},{"id":"2310.06522","title":"Watt For What: Rethinking Deep Learning's Energy-Performance Relationship","created":"2023-10-10","cited_by_count":16},{"id":"2003.04544","title":"Joint Parameter-and-Bandwidth Allocation for Improving the Efficiency of Partitioned Edge Learning","created":"2020-03-10","cited_by_count":15},{"id":"2111.12241","title":"Hierarchical Federated Learning based Anomaly Detection using Digital Twins for Smart Healthcare","created":"2021-11-24","cited_by_count":15},{"id":"2209.13080","title":"FedStack: Personalized activity monitoring using stacked federated learning","created":"2022-09-27","cited_by_count":15},{"id":"2009.02186","title":"Dynamic Scheduling for Stochastic Edge-Cloud Computing Environments using A3C learning and Residual Recurrent Neural Networks","created":"2020-09-01","cited_by_count":14},{"id":"2107.01349","title":"Split-and-Bridge: Adaptable Class Incremental Learning within a Single Neural Network","created":"2021-07-03","cited_by_count":14},{"id":"2301.10009","title":"Remote patient monitoring using artificial intelligence: Current state, applications, and challenges","created":"2023-01-19","cited_by_count":14},{"id":"2306.01811","title":"DVFO: Learning-Based DVFS for Energy-Efficient Edge-Cloud Collaborative Inference","created":"2023-06-02","cited_by_count":14},{"id":"2402.15351","title":"AutoMMLab: Automatically Generating Deployable Models from Language Instructions for Computer Vision Tasks","created":"2024-02-23","cited_by_count":14},{"id":"2103.15750","title":"Enabling Design Methodologies and Future Trends for Edge AI: Specialization and Co-design","created":"2021-03-25","cited_by_count":13},{"id":"2307.06148","title":"NetGPT: A Native-AI Network Architecture Beyond Provisioning Personalized Generative Services","created":"2023-07-12","cited_by_count":13},{"id":"2205.01423","title":"Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration","created":"2022-05-03","cited_by_count":12},{"id":"2205.04713","title":"Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures","created":"2022-05-10","cited_by_count":12},{"id":"2309.16398","title":"Recent Advances of Differential Privacy in Centralized Deep Learning: A Systematic Survey","created":"2023-09-28","cited_by_count":12},{"id":"2306.15333","title":"Shoggoth: Towards Efficient Edge-Cloud Collaborative Real-Time Video Inference via Adaptive Online Learning","created":"2023-06-27","cited_by_count":11},{"id":"2312.16279","title":"Cloud-Device Collaborative Learning for Multimodal Large Language Models","created":"2023-12-26","cited_by_count":11},{"id":"2408.06646","title":"Hybrid SD: Edge-Cloud Collaborative Inference for Stable Diffusion Models","created":"2024-08-13","cited_by_count":11},{"id":"2212.13791","title":"StyleID: Identity Disentanglement for Anonymizing Faces","created":"2022-12-28","cited_by_count":10},{"id":"2312.11489","title":"Agglomerative Federated Learning: Empowering Larger Model Training via End-Edge-Cloud Collaboration","created":"2023-12-01","cited_by_count":10},{"id":"2406.13399","title":"VELO: A Vector Database-Assisted Cloud-Edge Collaborative LLM QoS Optimization Framework","created":"2024-06-19","cited_by_count":10},{"id":"2008.03252","title":"A Survey on Security and Privacy Issues in Edge Computing-Assisted Internet of Things","created":"2020-08-05","cited_by_count":9},{"id":"2012.04436","title":"Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things","created":"2020-12-08","cited_by_count":9},{"id":"2311.16769","title":"Equilibrium in the Computing Continuum through Active Inference","created":"2023-11-28","cited_by_count":9},{"id":"2403.19178","title":"Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning","created":"2024-03-28","cited_by_count":9},{"id":"2404.00983","title":"Continual Learning for Smart City: A Survey","created":"2024-04-01","cited_by_count":9},{"id":"2404.01615","title":"Collaborative human-AI trust (CHAI-T): A process framework for active management of trust in human-AI collaboration","created":"2024-04-02","cited_by_count":9},{"id":"2404.14238","title":"Beyond the Edge: An Advanced Exploration of Reinforcement Learning for Mobile Edge Computing, its Applications, and Future Research Trajectories","created":"2024-04-22","cited_by_count":9},{"id":"2107.06946","title":"Towards Quantifying the Carbon Emissions of Differentially Private Machine Learning","created":"2021-07-14","cited_by_count":8},{"id":"2208.00761","title":"AI Augmented Edge and Fog Computing: Trends and Challenges","created":"2022-08-01","cited_by_count":7},{"id":"2307.11468","title":"Zero-touch realization of Pervasive Artificial Intelligence-as-a-service in 6G networks","created":"2023-07-21","cited_by_count":7},{"id":"2310.17944","title":"A Survey on Trustworthy Edge Intelligence: From Security and Reliability To Transparency and Sustainability","created":"2023-10-27","cited_by_count":7},{"id":"1908.01924","title":"Edge AIBench: Towards Comprehensive End-to-end Edge Computing Benchmarking","created":"2019-08-06","cited_by_count":6},{"id":"2005.02177","title":"CDC: Classification Driven Compression for Bandwidth Efficient Edge-Cloud Collaborative Deep Learning","created":"2020-05-04","cited_by_count":6},{"id":"2008.07235","title":"A Survey of Deep Learning for Data Caching in Edge Network","created":"2020-08-17","cited_by_count":6},{"id":"2104.13983","title":"Neuromorphic Computing is Turing-Complete","created":"2021-04-28","cited_by_count":6},{"id":"2105.03371","title":"The Synergy of Complex Event Processing and Tiny Machine Learning in Industrial IoT","created":"2021-05-04","cited_by_count":6},{"id":"2110.12415","title":"A Distributed Deep Reinforcement Learning Technique for Application Placement in Edge and Fog Computing Environments","created":"2021-10-24","cited_by_count":6},{"id":"2205.01081","title":"Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review","created":"2022-04-29","cited_by_count":6},{"id":"2309.07407","title":"Deep Reinforcement Learning-based Scheduling for Optimizing System Load and Response Time in Edge and Fog Computing Environments","created":"2023-09-14","cited_by_count":6},{"id":"2402.02521","title":"Neuromorphic hardware for sustainable AI data centers","created":"2024-02-04","cited_by_count":6},{"id":"2404.11420","title":"Quantum Cloud Computing: A Review, Open Problems, and Future Directions","created":"2024-04-17","cited_by_count":6},{"id":"2405.19635","title":"GKT: A Novel Guidance-Based Knowledge Transfer Framework For Efficient Cloud-edge Collaboration LLM Deployment","created":"2024-05-30","cited_by_count":6},{"id":"1801.05610","title":"A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing","created":"2018-01-17","cited_by_count":5},{"id":"1901.08946","title":"Joint Service Placement and Request Routing in Multi-cell Mobile Edge Computing Networks","created":"2019-01-25","cited_by_count":5},{"id":"2001.04041","title":"Secure V2V and V2I Communication in Intelligent Transportation using Cloudlets","created":"2020-01-13","cited_by_count":5},{"id":"2009.03473","title":"On the Self-Repair Role of Astrocytes in STDP Enabled Unsupervised SNNs","created":"2020-09-08","cited_by_count":5},{"id":"2202.10541","title":"Online Learning for Orchestration of Inference in Multi-User End-Edge-Cloud Networks","created":"2022-02-21","cited_by_count":5},{"id":"2205.10538","title":"Automated machine learning: AI-driven decision making in business analytics","created":"2022-05-21","cited_by_count":5},{"id":"2212.01698","title":"Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads","created":"2022-12-03","cited_by_count":5},{"id":"2401.01140","title":"Joint Offloading and Resource Allocation for Hybrid Cloud and Edge Computing in SAGINs: A Decision Assisted Hybrid Action Space Deep Reinforcement Learning Approach","created":"2024-01-02","cited_by_count":5},{"id":"2402.12702","title":"From Cloud to Edge: Rethinking Generative AI for Low-Resource Design Challenges","created":"2024-02-20","cited_by_count":5},{"id":"2408.09972","title":"Edge-Cloud Collaborative Motion Planning for Autonomous Driving with Large Language Models","created":"2024-08-19","cited_by_count":5},{"id":"2007.12557","title":"MPC-enabled Privacy-Preserving Neural Network Training against Malicious Attack","created":"2020-07-24","cited_by_count":4},{"id":"2012.10252","title":"LiveMap: Real-Time Dynamic Map in Automotive Edge Computing","created":"2020-12-16","cited_by_count":4},{"id":"2104.03368","title":"Exploring Task Placement for Edge-to-Cloud Applications using Emulation","created":"2021-04-07","cited_by_count":4},{"id":"2201.11837","title":"Resource Provisioning in Edge Computing for Latency Sensitive Applications","created":"2022-01-27","cited_by_count":4},{"id":"2206.11981","title":"Never trust, always verify : a roadmap for Trustworthy AI?","created":"2022-06-23","cited_by_count":4},{"id":"2207.01209","title":"Sustainable AI Processing at the Edge","created":"2022-07-04","cited_by_count":4},{"id":"2210.07842","title":"ENTS: An Edge-native Task Scheduling System for Collaborative Edge Computing","created":"2022-10-14","cited_by_count":4},{"id":"2306.06603","title":"Task-Oriented Integrated Sensing, Computation and Communication for Wireless Edge AI","created":"2023-06-11","cited_by_count":4}],"next_cursor":"100"}