Key papers

• Optimal Stabilizer Testing and Learning with Limited Quantum Memory (2026)
  Srinivasan Arunachalam et al.
  5.49
• Quantum-secure multiparty deep learning (2024)
  Kfir Sulimany et al.
  5.29
• Active Sensing for RIS-Aided Tracking and Power Control: A Hybrid Neuroevolution and Supervised Learning Approach (2026)
  George Stamatelis et al.
  4.39
• All-out Attack: Optimal Block Withholding Under Pay-Per-Share Scheme (2026)
  Mustafa Doger et al.
  4.39
• Secure Aggregation with Top-K Sparsification in Decentralized Federated Learning (2026)
  Hengxuan Tang et al.
  3.45
• Neilson's Weak vs. Strong Loss Aversion: A Characterization and a Generalized CPT-Utility Function (2026)
  Symeon Vaidanis et al.
  2.00
• From Score Approximation to Distribution Approximation in Score-Based Diffusion Models (2026)
  Lan V. Truong
  2.00
• The Capacity of Information-Theoretic Secure Aggregation in Federated Learning (2026)
  Lanxin Yi et al.
  1.94
• Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design (2026)
  Seyed Mohammad Azimi-Abarghouyi et al.
  1.89
• A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning (2026)
  Dario Filatrella et al.
  1.89
• Matching Rates and Optimal Allocation for Federated Probe-Logit Distillation under Heterogeneous Bandwidth Budgets (2026)
  Prasanjit Dubey and Xiaoming Huo
  1.89
• Secure Distributed Hypothesis Testing (2026)
  Gowtham R. Kurri et al.
  1.89
• Energy-Efficient Federated Edge Learning For Small-Scale Datasets in Large IoT Networks (2026)
  Haihui Xie et al.
  1.83
• Exploiting Correlations in Federated Learning: Opportunities and Practical Limitations (2026)
  Adrian Edin et al.
  1.83
• FB-NLL: A Feature-Based Approach to Tackle Noisy Labels in Personalized Federated Learning (2026)
  Abdulmoneam Ali and Ahmed Arafa
  1.83
• Decentralized Machine Learning with Centralized Performance Guarantees via Gibbs Algorithms (2026)
  Yaiza Bermudez et al.
  1.83
• Communication-Efficient Quantum Federated Learning over Large-Scale Wireless Networks (2026)
  Shaba Shaon et al.
  1.78
• FedCova: Robust Federated Covariance Learning Against Noisy Labels (2026)
  Xiangyu Zhong et al.
  1.78
• Prioritizing Gradient Sign Over Modulus: An Importance-Aware Framework for Wireless Federated Learning (2026)
  Yiyang Yue et al.
  1.78
• Quantum Key Distribution Secured Federated Learning for Channel Estimation and Radar Spectrum Sensing in 6G Networks (2026)
  Ferhat Ozgur Catak and Murat Kuzlu and Jungwon Seo and Umit Cali
  1.78
• A Theoretical Framework for Energy-Aware Gradient Pruning in Federated Learning (2026)
  Emmanouil M. Athanasakos
  1.78
• Age-Aware Edge-Blind Federated Learning via Over-the-Air Aggregation (2026)
  Ahmed M. Elshazly et al.
  1.72
• Secure Decentralized Pliable Index Coding for Target Data Size (2026)
  Anjali Padmanabhan et al.
  1.72
• Private Sum Computation: Trade-Offs between Communication, Randomness, and Privacy (2026)
  Remi A. Chou et al.
  1.72
• Energy-Efficient Over-the-Air Federated Learning via Pinching Antenna Systems (2026)
  Saba Asaad and Ali Bereyhi
  1.72
• Federated Latent Space Alignment for Multi-user Semantic Communications (2026)
  Giuseppe Di Poce et al.
  1.72
• CoCo-Fed: A Unified Framework for Memory- and Communication-Efficient Federated Learning at the Wireless Edge (2026)
  Zhiheng Guo et al.
  1.67
• Hybrid Federated Learning for Noise-Robust Training (2026)
  Yongjun Kim et al.
  1.67
• Lean Clients, Full Accuracy: Hybrid Zeroth- and First-Order Split Federated Learning (2026)
  Zhoubin Kou et al.
  1.67
• Post-Quantum Secure Aggregation via Code-Based Homomorphic Encryption (2026)
  Sebastian Bitzer et al.
  1.67
• Cross-Domain Federated Semantic Communication with Global Representation Alignment and Domain-Aware Aggregation (2025)
  Loc X. Nguyen et al.
  1.61
• Secure Over-the-Air Computation Against Multiple Eavesdroppers using Correlated Artificial Noise (2025)
  David Nordlund et al.
  1.61
• Feature-Based Semantics-Aware Scheduling for Energy-Harvesting Federated Learning (2025)
  Eunjeong Jeong et al.
  1.61
• Decentralized Fairness Aware Multi Task Federated Learning for VR Network (2025)
  Krishnendu S. Tharakan et al.
  1.61
• Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processing (2025)
  Seyed Mohammad Azimi-Abarghouyi et al.
  1.61
• Learned Digital Codes for Over-the-Air Computation in Federated Edge Learning (2025)
  Antonio Tarizzo et al.
  1.61
• Communication-Constrained Private Decentralized Online Personalized Mean Estimation (2025)
  Yauhen Yakimenka and Hsuan-Yin Lin and Eirik Rosnes and J\"org Kliewer
  1.56
• Computation-aware Energy-harvesting Federated Learning: Cyclic Scheduling with Selective Participation (2025)
  Eunjeong Jeong et al.
  1.56
• Trustworthy GenAI over 6G: Integrated Applications and Security Frameworks (2025)
  Bui Duc Son and Trinh Van Chien and Dong In Kim
  1.56
• Closing the Generalization Gap in Parameter-efficient Federated Edge Learning (2025)
  Xinnong Du and Zhonghao Lyu and Xiaowen Cao and Chunyang Wen and Shuguang Cui and Jie Xu
  1.56
• FedLoDrop: Federated LoRA with Dropout for Generalized LLM Fine-tuning (2025)
  Sijing Xie et al.
  1.50
• Statistical physics of deep learning: Optimal learning of a multi-layer perceptron near interpolation (2025)
  Jean Barbier et al.
  1.50
• Fed-PELAD: Communication-Efficient Federated Learning for Massive MIMO CSI Feedback with Personalized Encoders and a LoRA-Adapted Shared Decoder (2025)
  Yixiang Zhou et al.
  1.50
• Subgraph Federated Learning via Spectral Methods (2025)
  Javad Aliakbari and Johan \"Ostman and Ashkan Panahi and Alexandre Graell i Amat
  1.50
• Federated learning over physical channels: adaptive algorithms with near-optimal guarantees (2025)
  Rui Zhang et al.
  1.44
• Perfectly-Private Analog Secure Aggregation in Federated Learning (2025)
  Delio Jaramillo-Velez and Charul Rajput and Ragnar Freij-Hollanti and Camilla Hollanti and Alexandre Graell i Amat
  1.44
• Cost-Free Personalization via Information-Geometric Projection in Bayesian Federated Learning (2025)
  Nour Jamoussi et al.
  1.44
• Federated Multi-Agent Reinforcement Learning for Privacy-Preserving and Energy-Aware Resource Management in 6G Edge Networks (2025)
  Francisco Javier Esono Nkulu Andong and Qi Min
  1.44
• Distributed Batch Matrix Multiplication: Trade-Offs in Download Rate, Randomness, and Privacy (2025)
  Amirhosein Morteza and Remi A. Chou
  1.44
• A Federated Fine-Tuning Paradigm of Foundation Models in Heterogenous Wireless Networks (2025)
  Jingyi Wang et al.
  1.44
• Information-Theoretic Decentralized Secure Aggregation with Passive Collusion Resilience (2025)
  Xiang Zhang et al.
  1.39
• Energy-efficient Federated Learning for UAV Communications (2025)
  Chien-Wei Fu et al.
  1.39
• Communication-Learning Co-Design for Differentially Private Over-the-Air Federated Distillation (2025)
  Zihao Hu (1) et al.
  1.39
• Beyond Trade-offs: A Unified Framework for Privacy, Robustness, and Communication Efficiency in Federated Learning (2025)
  Yue Xia et al.
  1.39
• Robust Estimation Under Heterogeneous Corruption Rates (2025)
  Syomantak Chaudhuri et al.
  1.39
• Integrated Sensing, Communication, and Computation for Over-the-Air Federated Edge Learning (2025)
  Dingzhu Wen et al.
  1.39
• Straggler-Resilient Federated Learning over A Hybrid Conventional and Pinching Antenna Network (2025)
  Bibo Wu et al.
  1.39
• Tackling Federated Unlearning as a Parameter Estimation Problem (2025)
  Antonio Balordi et al.
  1.39
• ModShift: Model Privacy via Designed Shifts (2025)
  Nomaan A. Kherani et al.
  1.33
• Statistical mechanics of extensive-width Bayesian neural networks near interpolation (2025)
  Jean Barbier et al.
  1.22