{"total":120,"rows":[{"id":"2104.02151","title":"Distributed Learning in Wireless Networks: Recent Progress and Future Challenges","created":"2021-04-05","cited_by_count":129,"area":null},{"id":"2103.04505","title":"Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges","created":"2021-03-08","cited_by_count":115,"area":"inference"},{"id":"2209.05227","title":"DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization","created":"2022-09-12","cited_by_count":35,"area":null},{"id":"2312.00333","title":"Green Edge AI: A Contemporary Survey","created":"2023-12-01","cited_by_count":25,"area":null},{"id":"2206.04685","title":"Predictive Exit: Prediction of Fine-Grained Early Exits for Computation- and Energy-Efficient Inference","created":"2022-06-09","cited_by_count":24,"area":"inference"},{"id":"2207.07812","title":"A Survey on Collaborative DNN Inference for Edge Intelligence","created":"2022-07-16","cited_by_count":24,"area":null},{"id":"2112.09852","title":"LegoDNN: Block-grained Scaling of Deep Neural Networks for Mobile Vision","created":"2021-12-18","cited_by_count":20,"area":null},{"id":"2212.08343","title":"SplitGP: Achieving Both Generalization and Personalization in Federated Learning","created":"2022-12-16","cited_by_count":20,"area":null},{"id":"2105.01798","title":"Pervasive AI for IoT applications: A Survey on Resource-efficient Distributed Artificial Intelligence","created":"2021-05-04","cited_by_count":18,"area":null},{"id":"2105.12049","title":"Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs","created":"2021-05-25","cited_by_count":18,"area":null},{"id":"2105.13205","title":"Hamiltonian Deep Neural Networks Guaranteeing Non-vanishing Gradients by Design","created":"2021-05-27","cited_by_count":18,"area":null},{"id":"2301.00519","title":"Holistic Network Virtualization and Pervasive Network Intelligence for 6G","created":"2023-01-02","cited_by_count":14,"area":null},{"id":"2210.10514","title":"The Future of Consumer Edge-AI Computing","created":"2022-10-19","cited_by_count":12,"area":null},{"id":"2205.10635","title":"SplitPlace: AI Augmented Splitting and Placement of Large-Scale Neural Networks in Mobile Edge Environments","created":"2022-05-21","cited_by_count":11,"area":null},{"id":"2206.07269","title":"Resource-Constrained Edge AI with Early Exit Prediction","created":"2022-06-15","cited_by_count":11,"area":"inference"},{"id":"2210.17281","title":"GNN at the Edge: Cost-Efficient Graph Neural Network Processing over Distributed Edge Servers","created":"2022-10-31","cited_by_count":11,"area":null},{"id":"2408.06646","title":"Hybrid SD: Edge-Cloud Collaborative Inference for Stable Diffusion Models","created":"2024-08-13","cited_by_count":11,"area":"diffusion"},{"id":"2107.02466","title":"On-edge Multi-task Transfer Learning: Model and Practice with Data-driven Task Allocation","created":"2021-07-06","cited_by_count":9,"area":null},{"id":"2112.15131","title":"Resource-Efficient Deep Learning: A Survey on Model-, Arithmetic-, and Implementation-Level Techniques","created":"2021-12-30","cited_by_count":9,"area":null},{"id":"2301.07099","title":"Adaptive Deep Neural Network Inference Optimization with EENet","created":"2023-01-15","cited_by_count":9,"area":"inference"},{"id":"2307.10981","title":"PATROL: Privacy-Oriented Pruning for Collaborative Inference Against Model Inversion Attacks","created":"2023-07-20","cited_by_count":9,"area":null},{"id":"2603.16952","title":"Embodied Foundation Models at the Edge: A Survey of Deployment Constraints and Mitigation Strategies","created":"2026-03-16","cited_by_count":9,"area":null},{"id":"2105.11013","title":"Distributed CNN Inference on Resource-Constrained UAVs for Surveillance Systems: Design and Optimization","created":"2021-05-23","cited_by_count":8,"area":null},{"id":"2107.06304","title":"Privacy Vulnerability of Split Computing to Data-Free Model Inversion Attacks","created":"2021-07-13","cited_by_count":8,"area":null},{"id":"2108.09343","title":"Early-exit deep neural networks for distorted images: providing an efficient edge offloading","created":"2021-08-20","cited_by_count":8,"area":"inference"},{"id":"2109.03947","title":"SensiX++: Bringing MLOPs and Multi-tenant Model Serving to Sensory Edge Devices","created":"2021-09-08","cited_by_count":7,"area":null},{"id":"2112.09407","title":"Communication-oriented Model Fine-tuning for Packet-loss Resilient Distributed Inference under Highly Lossy IoT Networks","created":"2021-12-17","cited_by_count":7,"area":null},{"id":"2209.13443","title":"Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs","created":"2022-09-27","cited_by_count":6,"area":"inference"},{"id":"2212.03177","title":"Privacy-Preserving Visual Localization with Event Cameras","created":"2022-12-04","cited_by_count":6,"area":null},{"id":"2212.11201","title":"Deep Reinforcement Learning for Trajectory Path Planning and Distributed Inference in Resource-Constrained UAV Swarms","created":"2022-12-21","cited_by_count":6,"area":null},{"id":"2202.06084","title":"EREBA: Black-box Energy Testing of Adaptive Neural Networks","created":"2022-02-12","cited_by_count":5,"area":null},{"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,"area":null},{"id":"2301.00912","title":"Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semantics","created":"2023-01-03","cited_by_count":5,"area":null},{"id":"2302.07734","title":"TFormer: A Transmission-Friendly ViT Model for IoT Devices","created":"2023-02-15","cited_by_count":5,"area":null},{"id":"2303.02384","title":"Hierarchical Training of Deep Neural Networks Using Early Exiting","created":"2023-03-04","cited_by_count":5,"area":null},{"id":"2303.08581","title":"Model Extraction Attacks on Split Federated Learning","created":"2023-03-13","cited_by_count":5,"area":null},{"id":"2412.10448","title":"Unlocking Visual Secrets: Inverting Features with Diffusion Priors for Image Reconstruction","created":"2024-12-11","cited_by_count":5,"area":"diffusion"},{"id":"2511.21669","title":"DSD: A Distributed Speculative Decoding Solution for Edge-Cloud Agile Large Model Serving","created":"2025-11-26","cited_by_count":5,"area":"inference"},{"id":"2208.13032","title":"RL-DistPrivacy: Privacy-Aware Distributed Deep Inference for low latency IoT systems","created":"2022-08-27","cited_by_count":4,"area":null},{"id":"2303.06246","title":"Zone-based Federated Learning for Mobile Sensing Data","created":"2023-03-10","cited_by_count":4,"area":null},{"id":"2408.05247","title":"Early-Exit meets Model-Distributed Inference at Edge Networks","created":"2024-08-08","cited_by_count":4,"area":"inference"},{"id":"2503.21476","title":"Robust DNN Partitioning and Resource Allocation Under Uncertain Inference Time","created":"2025-03-27","cited_by_count":4,"area":null},{"id":"2605.23158","title":"What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference","created":"2026-05-22","cited_by_count":4,"area":null},{"id":"2101.05952","title":"Dynamic DNN Decomposition for Lossless Synergistic Inference","created":"2021-01-15","cited_by_count":3,"area":null},{"id":"2105.06250","title":"3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low BitwidthQuantization, and Ultra-Low Latency Acceleration","created":"2021-05-11","cited_by_count":3,"area":null},{"id":"2107.04648","title":"Efficient Real-Time Image Recognition Using Collaborative Swarm of UAVs and Convolutional Networks","created":"2021-07-09","cited_by_count":3,"area":null},{"id":"2108.03872","title":"Adaptive Anomaly Detection for Internet of Things in Hierarchical Edge Computing: A Contextual-Bandit Approach","created":"2021-08-09","cited_by_count":3,"area":null},{"id":"2111.08206","title":"JMSNAS: Joint Model Split and Neural Architecture Search for Learning over Mobile Edge Networks","created":"2021-11-16","cited_by_count":3,"area":null},{"id":"2201.06769","title":"DEFER: Distributed Edge Inference for Deep Neural Networks","created":"2022-01-18","cited_by_count":3,"area":null},{"id":"2208.02597","title":"Edge-centric Optimization of Multi-modal ML-driven eHealth Applications","created":"2022-08-04","cited_by_count":3,"area":null},{"id":"2304.10020","title":"A Survey on Deep Neural Network Partition over Cloud, Edge and End Devices","created":"2023-04-20","cited_by_count":3,"area":null},{"id":"2305.15858","title":"LLHR: Low Latency and High Reliability CNN Distributed Inference for Resource-Constrained UAV Swarms","created":"2023-05-25","cited_by_count":3,"area":null},{"id":"2312.16497","title":"Mobility and Cost Aware Inference Accelerating Algorithm for Edge Intelligence","created":"2023-12-27","cited_by_count":3,"area":null},{"id":"2403.17154","title":"On the Impact of Black-box Deployment Strategies for Edge AI on Latency and Model Performance","created":"2024-03-25","cited_by_count":3,"area":null},{"id":"2603.23791","title":"The Cognitive Firewall:Securing Browser Based AI Agents Against Indirect Prompt Injection Via Hybrid Edge Cloud Defense","created":"2026-03-24","cited_by_count":3,"area":"agents"},{"id":"2109.06440","title":"Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems","created":"2021-09-14","cited_by_count":2,"area":null},{"id":"2208.00485","title":"Adaptive Edge Offloading for Image Classification Under Rate Limit","created":"2022-07-31","cited_by_count":2,"area":null},{"id":"2302.11180","title":"DISCO: Distributed Inference with Sparse Communications","created":"2023-02-22","cited_by_count":2,"area":null},{"id":"2303.08970","title":"Gated Compression Layers for Efficient Always-On Models","created":"2023-03-15","cited_by_count":2,"area":null},{"id":"2404.13348","title":"Socialized Learning: A Survey of the Paradigm Shift for Edge Intelligence in Networked Systems","created":"2024-04-20","cited_by_count":2,"area":null},{"id":"2405.15079","title":"A Survey of Distributed Learning in Cloud, Mobile, and Edge Settings","created":"2024-05-23","cited_by_count":2,"area":null},{"id":"2411.10500","title":"Edge-Only Universal Adversarial Attacks in Distributed Learning","created":"2024-11-15","cited_by_count":2,"area":null},{"id":"2412.12371","title":"Priority-Aware Model-Distributed Inference at Edge Networks","created":"2024-12-16","cited_by_count":2,"area":null},{"id":"2501.02508","title":"PTEENet: Post-Trained Early-Exit Neural Networks Augmentation for Inference Cost Optimization","created":"2025-01-05","cited_by_count":2,"area":"inference"},{"id":"2504.15300","title":"Collaborative Learning of On-Device Small Model and Cloud-Based Large Model: Advances and Future Directions","created":"2025-04-17","cited_by_count":2,"area":null},{"id":"2511.15316","title":"What Your Features Reveal: Data-Efficient Black-Box Feature Inversion Attack for Split DNNs","created":"2025-11-19","cited_by_count":2,"area":null},{"id":"2601.20742","title":"Compression Tells Intelligence: Visual Coding, Visual Token Technology, and the Unification","created":"2026-01-28","cited_by_count":2,"area":null},{"id":"2107.04767","title":"Anomaly Detection in Residential Video Surveillance on Edge Devices in IoT Framework","created":"2021-07-10","cited_by_count":1,"area":null},{"id":"2109.08231","title":"RAPID-RL: A Reconfigurable Architecture with Preemptive-Exits for Efficient Deep-Reinforcement Learning","created":"2021-09-16","cited_by_count":1,"area":null},{"id":"2202.02310","title":"EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators","created":"2022-02-04","cited_by_count":1,"area":null},{"id":"2206.05267","title":"CONTINUER: Maintaining Distributed DNN Services During Edge Failures","created":"2022-04-25","cited_by_count":1,"area":null},{"id":"2207.12113","title":"AutoDiCE: Fully Automated Distributed CNN Inference at the Edge","created":"2022-07-20","cited_by_count":1,"area":null},{"id":"2207.12866","title":"Implementation Of Tiny Machine Learning Models On Arduino 33 BLE For Gesture And Speech Recognition","created":"2022-07-23","cited_by_count":1,"area":null},{"id":"2308.06515","title":"Seed Feature Maps-based CNN Models for LEO Satellite Remote Sensing Services","created":"2023-08-12","cited_by_count":1,"area":null},{"id":"2308.08709","title":"Dynamic Neural Network is All You Need: Understanding the Robustness of Dynamic Mechanisms in Neural Networks","created":"2023-08-17","cited_by_count":1,"area":null},{"id":"2311.16851","title":"Edge AI for Internet of Energy: Challenges and Perspectives","created":"2023-11-28","cited_by_count":1,"area":null},{"id":"2402.15006","title":"opp/ai: Optimistic Privacy-Preserving AI on Blockchain","created":"2024-02-22","cited_by_count":1,"area":null},{"id":"2410.09747","title":"t-READi: Transformer-Powered Robust and Efficient Multimodal Inference for Autonomous Driving","created":"2024-10-13","cited_by_count":1,"area":null},{"id":"2411.01548","title":"Analysis of regularized federated learning","created":"2024-11-03","cited_by_count":1,"area":null},{"id":"2505.08793","title":"Onboard Optimization and Learning: A Survey","created":"2025-05-07","cited_by_count":1,"area":null},{"id":"2505.12566","title":"HybridServe: Efficient Serving of Large AI Models with Confidence-Based Cascade Routing","created":"2025-05-18","cited_by_count":1,"area":null},{"id":"2512.19726","title":"Tiny, On-Device Decision Makers with the MiniConv Library","created":"2025-12-17","cited_by_count":1,"area":"deeprl"},{"id":"2602.04120","title":"Scalable Explainability-as-a-Service (XaaS) for Edge AI Systems","created":"2026-02-04","cited_by_count":1,"area":null},{"id":"2606.20591","title":"Delay-Adaptive Speculation Control for Low-Latency Edge-Cloud LLM Inference","created":"2026-05-17","cited_by_count":1,"area":"inference"},{"id":"2608.28691","title":"Defending Wearable VLMs Against Private Attribute Inference","created":"2026-08-26","cited_by_count":1,"area":null},{"id":"2102.05021","title":"Consensus Based Multi-Layer Perceptrons for Edge Computing","created":"2021-02-09","cited_by_count":0,"area":null},{"id":"2106.12810","title":"A Construction Kit for Efficient Low Power Neural Network Accelerator Designs","created":"2021-06-24","cited_by_count":0,"area":null},{"id":"2108.02872","title":"Understanding Human Innate Immune System Dependencies using Graph Neural Networks","created":"2021-08-05","cited_by_count":0,"area":null},{"id":"2109.12400","title":"Communication-Efficient Federated Linear and Deep Generalized Canonical Correlation Analysis","created":"2021-09-25","cited_by_count":0,"area":null},{"id":"2110.02724","title":"ParaDiS: Parallelly Distributable Slimmable Neural Networks","created":"2021-10-06","cited_by_count":0,"area":null},{"id":"2111.02489","title":"Communication-Efficient Separable Neural Network for Distributed Inference on Edge Devices","created":"2021-11-03","cited_by_count":0,"area":null},{"id":"2206.08152","title":"Fault-Tolerant Collaborative Inference through the Edge-PRUNE Framework","created":"2022-06-16","cited_by_count":0,"area":null},{"id":"2208.07643","title":"A Review of the Convergence of 5G/6G Architecture and Deep Learning","created":"2022-08-16","cited_by_count":0,"area":null},{"id":"2210.05182","title":"Edge-Cloud Cooperation for DNN Inference via Reinforcement Learning and Supervised Learning","created":"2022-10-11","cited_by_count":0,"area":null},{"id":"2210.07750","title":"Bandwidth-efficient distributed neural network architectures with application to body sensor networks","created":"2022-10-14","cited_by_count":0,"area":null},{"id":"2212.04223","title":"Vicious Classifiers: Assessing Inference-time Data Reconstruction Risk in Edge Computing","created":"2022-12-08","cited_by_count":0,"area":null},{"id":"2301.01758","title":"An Ensemble Mobile-Cloud Computing Method for Affordable and Accurate Glucometer Readout","created":"2023-01-04","cited_by_count":0,"area":null},{"id":"2302.00623","title":"Accordion: A Communication-Aware Machine Learning Framework for Next Generation Networks","created":"2023-01-12","cited_by_count":0,"area":null},{"id":"2307.05232","title":"A Survey From Distributed Machine Learning to Distributed Deep Learning","created":"2023-07-11","cited_by_count":0,"area":null},{"id":"2310.19112","title":"Efficient IoT Inference via Context-Awareness","created":"2023-10-29","cited_by_count":0,"area":null}],"next_cursor":"100"}