{"total":52,"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":"2102.04170","title":"Learning Task-Oriented Communication for Edge Inference: An Information Bottleneck Approach","created":"2021-02-08","cited_by_count":110,"area":null},{"id":"2111.12444","title":"Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications","created":"2021-11-24","cited_by_count":97,"area":null},{"id":"2306.12194","title":"Split Learning in 6G Edge Networks","created":"2023-06-21","cited_by_count":68,"area":null},{"id":"2307.02779","title":"Large Language Models Empowered Autonomous Edge AI for Connected Intelligence","created":"2023-07-06","cited_by_count":56,"area":null},{"id":"2109.00172","title":"Task-Oriented Communication for Multi-Device Cooperative Edge Inference","created":"2021-09-01","cited_by_count":52,"area":null},{"id":"2411.12469","title":"AI Flow at the Network Edge","created":"2024-11-19","cited_by_count":46,"area":null},{"id":"2405.17053","title":"WirelessLLM: Empowering Large Language Models Towards Wireless Intelligence","created":"2024-05-27","cited_by_count":44,"area":null},{"id":"2506.12479","title":"AI Flow: Perspectives, Scenarios, and Approaches","created":"2025-06-14","cited_by_count":44,"area":null},{"id":"2207.00969","title":"Task-Oriented Sensing, Computation, and Communication Integration for Multi-Device Edge AI","created":"2022-07-03","cited_by_count":33,"area":null},{"id":"2312.00333","title":"Green Edge AI: A Contemporary Survey","created":"2023-12-01","cited_by_count":25,"area":null},{"id":"2105.13618","title":"Optimal Model Placement and Online Model Splitting for Device-Edge Co-Inference","created":"2021-05-28","cited_by_count":19,"area":null},{"id":"2301.03377","title":"Machine Learning for Large-Scale Optimization in 6G Wireless Networks","created":"2023-01-03","cited_by_count":18,"area":null},{"id":"2104.09286","title":"Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems","created":"2021-04-15","cited_by_count":14,"area":null},{"id":"2211.01255","title":"Task-Oriented Over-the-Air Computation for Multi-Device Edge AI","created":"2022-11-02","cited_by_count":14,"area":null},{"id":"2304.14271","title":"A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services","created":"2023-04-13","cited_by_count":14,"area":null},{"id":"2211.14049","title":"Task-Oriented Communication for Edge Video Analytics","created":"2022-11-25","cited_by_count":13,"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":"2206.06304","title":"Multi-user Co-inference with Batch Processing Capable Edge Server","created":"2022-06-03","cited_by_count":11,"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":"2404.07217","title":"Attention-aware Semantic Communications for Collaborative Inference","created":"2024-02-23","cited_by_count":7,"area":null},{"id":"2105.00591","title":"Single-Training Collaborative Object Detectors Adaptive to Bandwidth and Computation","created":"2021-05-03","cited_by_count":6,"area":null},{"id":"2411.06773","title":"Model Partition and Resource Allocation for Split Learning in Vehicular Edge Networks","created":"2024-11-11","cited_by_count":6,"area":null},{"id":"2110.02912","title":"Generative Optimization Networks for Memory Efficient Data Generation","created":"2021-10-06","cited_by_count":5,"area":null},{"id":"2210.03555","title":"In-situ Model Downloading to Realize Versatile Edge AI in 6G Mobile Networks","created":"2022-10-07","cited_by_count":5,"area":null},{"id":"2307.15316","title":"Efficient Multiuser AI Downloading via Reusable Knowledge Broadcasting","created":"2023-07-28","cited_by_count":5,"area":null},{"id":"2404.06007","title":"Collaborative Edge AI Inference over Cloud-RAN","created":"2024-04-09","cited_by_count":5,"area":null},{"id":"2410.19375","title":"COMSPLIT: A Communication-Aware Split Learning Design for Heterogeneous IoT Platforms","created":"2024-10-25","cited_by_count":5,"area":null},{"id":"2411.18199","title":"Semantic Edge Computing and Semantic Communications in 6G Networks: A Unifying Survey and Research Challenges","created":"2024-11-27","cited_by_count":5,"area":null},{"id":"2504.03686","title":"Revisiting Outage for Edge Inference Systems","created":"2025-03-22","cited_by_count":5,"area":null},{"id":"2503.22982","title":"PartialLoading: User Scheduling and Bandwidth Allocation for Parameter-sharing Edge Inference","created":"2025-03-29","cited_by_count":4,"area":null},{"id":"2203.07140","title":"CAROL: Confidence-Aware Resilience Model for Edge Federations","created":"2022-03-14","cited_by_count":3,"area":null},{"id":"2306.12691","title":"Slimmable Encoders for Flexible Split DNNs in Bandwidth and Resource Constrained IoT Systems","created":"2023-06-22","cited_by_count":3,"area":null},{"id":"2108.13009","title":"Communication-Computation Efficient Device-Edge Co-Inference via AutoML","created":"2021-08-30","cited_by_count":2,"area":null},{"id":"2208.07658","title":"DRAGON: Decentralized Fault Tolerance in Edge Federations","created":"2022-08-16","cited_by_count":2,"area":null},{"id":"2502.16091","title":"Privacy-Aware Joint DNN Model Deployment and Partitioning Optimization for Collaborative Edge Inference Services","created":"2025-02-22","cited_by_count":2,"area":null},{"id":"2401.00445","title":"Energy-Efficient Power Control for Multiple-Task Split Inference in UAVs: A Tiny Learning-Based Approach","created":"2023-12-31","cited_by_count":1,"area":null},{"id":"2407.00955","title":"Task-oriented Over-the-air Computation for Edge-device Co-inference with Balanced Classification Accuracy","created":"2024-07-01","cited_by_count":1,"area":null},{"id":"2410.08651","title":"Edge AI Collaborative Learning: Bayesian Approaches to Uncertainty Estimation","created":"2024-10-11","cited_by_count":1,"area":null},{"id":"2412.00862","title":"Toward Real-Time Edge AI: Model-Agnostic Task-Oriented Communication with Visual Feature Alignment","created":"2024-12-01","cited_by_count":1,"area":null},{"id":"2502.15472","title":"Aligning Task- and Reconstruction-Oriented Communications for Edge Intelligence","created":"2025-02-21","cited_by_count":1,"area":null},{"id":"2504.03052","title":"Cooperative Inference for Real-Time 3D Human Pose Estimation in Multi-Device Edge Networks","created":"2025-04-03","cited_by_count":1,"area":null},{"id":"2605.07354","title":"Task-Oriented Communication for Human Action Understanding via Edge-Cloud Co-Inference","created":"2026-05-08","cited_by_count":1,"area":null},{"id":"2203.02892","title":"Watch from sky: machine-learning-based multi-UAV network for predictive police surveillance","created":"2022-03-06","cited_by_count":0,"area":null},{"id":"2211.07860","title":"Enabling AI Quality Control via Feature Hierarchical Edge Inference","created":"2022-11-15","cited_by_count":0,"area":null},{"id":"2301.03133","title":"Transceiver Cooperative Learning-aided Semantic Communications Against Mismatched Background Knowledge Bases","created":"2023-01-09","cited_by_count":0,"area":null},{"id":"2503.08661","title":"Task-Oriented Co-Design of Communication, Computing, and Control for Edge-Enabled Industrial Cyber-Physical Systems","created":"2025-03-11","cited_by_count":0,"area":null},{"id":"2601.10915","title":"A PAC-Bayesian Analysis of Channel-Induced Degradation in Edge Inference","created":"2026-01-16","cited_by_count":0,"area":null},{"id":"2603.03146","title":"Channel-Adaptive Edge AI: Maximizing Inference Throughput by Adapting Computational Complexity to Channel States","created":"2026-03-03","cited_by_count":0,"area":null},{"id":"2604.09681","title":"R2E-VID: Two-Stage Robust Routing via Temporal Gating for Elastic Edge-Cloud Video Inference","created":"2026-04-03","cited_by_count":0,"area":null},{"id":"2604.19623","title":"SAGE: Training-Free Semantic Evidence Composition for Edge-Cloud Inference under Hard Uplink Budgets","created":"2026-04-21","cited_by_count":0,"area":null},{"id":"2607.29659","title":"GQ-FSL: Green Quantized Federated Split Learning Framework for Wireless Edge Networks","created":"2026-07-31","cited_by_count":0,"area":null}],"next_cursor":null}