{"total":95,"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":"2303.15991","title":"Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks","created":"2023-03-26","cited_by_count":95,"area":null},{"id":"2403.13101","title":"AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks","created":"2024-03-19","cited_by_count":64,"area":null},{"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,"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":"2101.12704","title":"Federated Learning over Wireless Device-to-Device Networks: Algorithms and Convergence Analysis","created":"2021-01-29","cited_by_count":51,"area":null},{"id":"2103.14272","title":"Hierarchical Federated Learning with Quantization: Convergence Analysis and System Design","created":"2021-03-26","cited_by_count":47,"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":"2106.09397","title":"Quantized Federated Learning under Transmission Delay and Outage Constraints","created":"2021-06-17","cited_by_count":37,"area":null},{"id":"2106.00490","title":"Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy Constraints","created":"2021-05-31","cited_by_count":36,"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":"2110.13041","title":"Applications and Techniques for Fast Machine Learning in Science","created":"2021-10-25","cited_by_count":32,"area":null},{"id":"2102.13604","title":"Federated Edge Learning with Misaligned Over-The-Air Computation","created":"2021-02-26","cited_by_count":30,"area":null},{"id":"2312.00333","title":"Green Edge AI: A Contemporary Survey","created":"2023-12-01","cited_by_count":25,"area":null},{"id":"2106.15734","title":"UAV-assisted Online Machine Learning over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach","created":"2021-06-29","cited_by_count":20,"area":null},{"id":"2111.15071","title":"Communication-Efficient Federated Learning via Quantized Compressed Sensing","created":"2021-11-30","cited_by_count":18,"area":null},{"id":"2202.02947","title":"Parallel Successive Learning for Dynamic Distributed Model Training over Heterogeneous Wireless Networks","created":"2022-02-07","cited_by_count":18,"area":null},{"id":"2205.13054","title":"Scalable and Low-Latency Federated Learning with Cooperative Mobile Edge Networking","created":"2022-05-25","cited_by_count":18,"area":null},{"id":"2307.10805","title":"Communication-Efficient Split Learning via Adaptive Feature-Wise Compression","created":"2023-07-20","cited_by_count":18,"area":null},{"id":"2104.03490","title":"Joint Optimization of Communications and Federated Learning Over the Air","created":"2021-04-08","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":"2106.15905","title":"Faithful Edge Federated Learning: Scalability and Privacy","created":"2021-06-30","cited_by_count":13,"area":null},{"id":"2110.11775","title":"Federated Learning over Wireless IoT Networks with Optimized Communication and Resources","created":"2021-10-22","cited_by_count":13,"area":null},{"id":"2211.14049","title":"Task-Oriented Communication for Edge Video Analytics","created":"2022-11-25","cited_by_count":13,"area":null},{"id":"2210.13111","title":"Federated Learning and Meta Learning: Approaches, Applications, and Directions","created":"2022-10-24","cited_by_count":12,"area":null},{"id":"2408.08074","title":"A Survey on Integrated Sensing, Communication, and Computation","created":"2024-08-15","cited_by_count":12,"area":null},{"id":"2102.07972","title":"Federated Learning over Wireless Networks: A Band-limited Coordinated Descent Approach","created":"2021-02-16","cited_by_count":11,"area":null},{"id":"2201.08512","title":"Vertical Federated Edge Learning with Distributed Integrated Sensing and Communication","created":"2022-01-21","cited_by_count":11,"area":null},{"id":"2209.02428","title":"Predictive GAN-powered Multi-Objective Optimization for Hybrid Federated Split Learning","created":"2022-09-02","cited_by_count":11,"area":null},{"id":"2101.03627","title":"Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks","created":"2021-01-10","cited_by_count":10,"area":null},{"id":"2102.12357","title":"Wirelessly Powered Federated Edge Learning: Optimal Tradeoffs Between Convergence and Power Transfer","created":"2021-02-24","cited_by_count":10,"area":null},{"id":"2103.02270","title":"Temporal-Structure-Assisted Gradient Aggregation for Over-the-Air Federated Edge Learning","created":"2021-03-03","cited_by_count":10,"area":null},{"id":"2306.12212","title":"MimiC: Combating Client Dropouts in Federated Learning by Mimicking Central Updates","created":"2023-06-21","cited_by_count":10,"area":null},{"id":"2305.05933","title":"Spectrum Breathing: Protecting Over-the-Air Federated Learning Against Interference","created":"2023-05-10","cited_by_count":9,"area":null},{"id":"2101.02198","title":"Federated Learning over Noisy Channels: Convergence Analysis and Design Examples","created":"2021-01-06","cited_by_count":8,"area":null},{"id":"2301.00433","title":"Optimization of Image Transmission in a Cooperative Semantic Communication Networks","created":"2023-01-01","cited_by_count":8,"area":null},{"id":"2106.12561","title":"Fine-Grained Data Selection for Improved Energy Efficiency of Federated Edge Learning","created":"2021-06-20","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":"2405.09514","title":"Tackling Distribution Shifts in Task-Oriented Communication with Information Bottleneck","created":"2024-05-15","cited_by_count":7,"area":null},{"id":"2110.09660","title":"BEV-SGD: Best Effort Voting SGD for Analog Aggregation Based Federated Learning against Byzantine Attackers","created":"2021-10-18","cited_by_count":6,"area":null},{"id":"2202.02727","title":"Energy-Aware Edge Association for Cluster-based Personalized Federated Learning","created":"2022-02-06","cited_by_count":6,"area":null},{"id":"2107.09574","title":"Accelerating Edge Intelligence via Integrated Sensing and Communication","created":"2021-07-20","cited_by_count":5,"area":null},{"id":"2210.02235","title":"Over-the-Air Federated Learning with Privacy Protection via Correlated Additive Perturbations","created":"2022-10-05","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":"2504.03686","title":"Revisiting Outage for Edge Inference Systems","created":"2025-03-22","cited_by_count":5,"area":null},{"id":"2104.06990","title":"Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges","created":"2021-04-14","cited_by_count":4,"area":null},{"id":"2106.01958","title":"Multiplierless MP-Kernel Machine For Energy-efficient Edge Devices","created":"2021-06-03","cited_by_count":4,"area":null},{"id":"2202.06105","title":"On Federated Learning with Energy Harvesting Clients","created":"2022-02-12","cited_by_count":4,"area":null},{"id":"2311.16741","title":"Asynchronous Wireless Federated Learning with Probabilistic Client Selection","created":"2023-11-28","cited_by_count":4,"area":null},{"id":"2312.04688","title":"Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights","created":"2023-12-07","cited_by_count":4,"area":null},{"id":"2407.09873","title":"Resource Management for Low-latency Cooperative Fine-tuning of Foundation Models at the Network Edge","created":"2024-07-13","cited_by_count":4,"area":null},{"id":"2111.13526","title":"An Optimization Framework for Federated Edge Learning","created":"2021-11-26","cited_by_count":3,"area":null},{"id":"2202.13932","title":"Leveraging Channel Noise for Sampling and Privacy via Quantized Federated Langevin Monte Carlo","created":"2022-02-28","cited_by_count":3,"area":null},{"id":"2203.10923","title":"TinyMLOps: Operational Challenges for Widespread Edge AI Adoption","created":"2022-03-21","cited_by_count":3,"area":null},{"id":"2405.04875","title":"SCALA: Split Federated Learning with Concatenated Activations and Logit Adjustments","created":"2024-05-08","cited_by_count":3,"area":null},{"id":"2406.16929","title":"Modelling the 5G Energy Consumption using Real-world Data: Energy Fingerprint is All You Need","created":"2024-06-13","cited_by_count":3,"area":null},{"id":"2412.04783","title":"KNN-MMD: Cross Domain Wireless Sensing via Local Distribution Alignment","created":"2024-12-06","cited_by_count":3,"area":null},{"id":"2505.10405","title":"Visual Fidelity Index for Generative Semantic Communications with Critical Information Embedding","created":"2025-05-15","cited_by_count":3,"area":null},{"id":"2509.12141","title":"When MoE Meets Blockchain: A Trustworthy Distributed Framework of Large Models","created":"2025-09-15","cited_by_count":3,"area":"moe"},{"id":"2601.00644","title":"FlexSpec: Frozen Drafts Meet Evolving Targets in Edge-Cloud Collaborative LLM Speculative Decoding","created":"2026-01-02","cited_by_count":3,"area":"inference"},{"id":"2605.00515","title":"SpaceMoE: Realizing Distributed Mixture-of-Experts Inference over Space Networks","created":"2026-05-01","cited_by_count":3,"area":"moe"},{"id":"2104.05509","title":"Threshold-Based Data Exclusion Approach for Energy-Efficient Federated Edge Learning","created":"2021-03-30","cited_by_count":2,"area":null},{"id":"2107.11588","title":"Accelerating Federated Edge Learning via Optimized Probabilistic Device Scheduling","created":"2021-07-24","cited_by_count":2,"area":null},{"id":"2402.11925","title":"Energy-Efficient Edge Learning via Joint Data Deepening-and-Prefetching","created":"2024-02-19","cited_by_count":2,"area":null},{"id":"2407.07739","title":"UAV-assisted Unbiased Hierarchical Federated Learning: Performance and Convergence Analysis","created":"2024-07-05","cited_by_count":2,"area":null},{"id":"2109.00757","title":"Energy-Efficient Multi-Orchestrator Mobile Edge Learning","created":"2021-09-02","cited_by_count":1,"area":null},{"id":"2111.10267","title":"Over-the-Air Federated Learning with Retransmissions (Extended Version)","created":"2021-11-19","cited_by_count":1,"area":null},{"id":"2211.00481","title":"Multi-Resource Allocation for On-Device Distributed Federated Learning Systems","created":"2022-11-01","cited_by_count":1,"area":null},{"id":"2303.17885","title":"Accelerating Wireless Federated Learning via Nesterov's Momentum and Distributed Principle Component Analysis","created":"2023-03-31","cited_by_count":1,"area":null},{"id":"2310.05076","title":"Towards Scalable Wireless Federated Learning: Challenges and Solutions","created":"2023-10-08","cited_by_count":1,"area":null},{"id":"2311.14401","title":"Prototype of deployment of Federated Learning with IoT devices","created":"2023-11-24","cited_by_count":1,"area":null},{"id":"2312.10411","title":"Towards Reliable Participation in UAV-Enabled Federated Edge Learning on Non-IID Data","created":"2023-12-16","cited_by_count":1,"area":null},{"id":"2412.14668","title":"LoLaFL: Low-Latency Federated Learning via Forward-only Propagation","created":"2024-12-19","cited_by_count":1,"area":null},{"id":"2504.14947","title":"AGI-Driven Generative Semantic Communications: Principles and Practices","created":"2025-04-21","cited_by_count":1,"area":null},{"id":"2507.15769","title":"Multi-Modal Sensor Fusion for Proactive Blockage Prediction in mmWave Vehicular Networks","created":"2025-07-21","cited_by_count":1,"area":null},{"id":"2508.17957","title":"Generative Feature Imputing -- A Technique for Error-resilient Semantic Communication","created":"2025-08-25","cited_by_count":1,"area":null},{"id":"2103.03444","title":"Optimization of User Selection and Bandwidth Allocation for Federated Learning in VLC/RF Systems","created":"2021-03-05","cited_by_count":0,"area":null},{"id":"2202.12683","title":"Bridging the Urban-Rural Connectivity Gap through Intelligent Space, Air, and Ground Networks","created":"2022-02-25","cited_by_count":0,"area":null},{"id":"2212.13141","title":"Beyond 5G Networks: Integration of Communication, Computing, Caching, and Control","created":"2022-12-26","cited_by_count":0,"area":null},{"id":"2308.09082","title":"Over-the-Air Computation Aided Federated Learning with the Aggregation of Normalized Gradient","created":"2023-08-17","cited_by_count":0,"area":null},{"id":"2309.10878","title":"DeepliteRT: Computer Vision at the Edge","created":"2023-09-19","cited_by_count":0,"area":null},{"id":"2309.13643","title":"REWAFL: Residual Energy and Wireless Aware Participant Selection for Efficient Federated Learning over Mobile Devices","created":"2023-09-24","cited_by_count":0,"area":null},{"id":"2403.18946","title":"Random Aggregate Beamforming for Over-the-Air Federated Learning in Large-Scale Networks","created":"2024-02-20","cited_by_count":0,"area":null},{"id":"2510.20518","title":"Adversary-Aware Private Inference over Wireless Channels","created":"2025-10-23","cited_by_count":0,"area":null},{"id":"2511.01433","title":"CG-FKAN: Compressed-Grid Federated Kolmogorov-Arnold Networks for Communication Constrained Environment","created":"2025-11-03","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":"2601.14942","title":"Communication-Efficient Multi-Modal Edge Inference via Uncertainty-Aware Distributed Learning","created":"2026-01-21","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":"2604.25018","title":"Internet of Everything in the 6G Era: Paradigms, Enablers, Potentials and Future Directions","created":"2026-04-27","cited_by_count":0,"area":null},{"id":"2606.01015","title":"AI-IoT-Robotics Integration: Survey of Frameworks, Emerging Trends, and the Path Toward Connected Robotics","created":"2026-05-31","cited_by_count":0,"area":null},{"id":"2606.04581","title":"Multi-SPIN: Multi-Access Speculative Inference for Cooperative Token Generation at the Edge","created":"2026-06-03","cited_by_count":0,"area":"inference"},{"id":"2607.28907","title":"Domain-Adaptive Deep Joint Source-Channel Coding for Image Classification","created":"2026-07-31","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},{"id":"2608.13961","title":"Polar Code Based Federated Learning: Convergence Analysis and Resource Allocation","created":"2026-08-14","cited_by_count":0,"area":null}],"next_cursor":null}