Imagen de Portada

ELSA: Efficient LLM-Centric Split Aggregation for Privacy-Aware Hierarchical Federated Learning over the Network Edge

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Yang, Xiaohong, Xie, Tong, Liwang, Minghui, Shang, Chikai, Lu, Yang, Jiao, Zhenzhen, Fu, Liqun, Hosseinalipour, Seyyedali
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning
por: Yang, Xiaohong, et al.
Publicado: (2025)

Adaptive UAV-Assisted Hierarchical Federated Learning: Optimizing Energy, Latency, and Resilience for Dynamic Smart IoT
por: Yang, Xiaohong, et al.
Publicado: (2025)

Towards Seamless Hierarchical Federated Learning under Intermittent Client Participation: A Stagewise Decision-Making Methodology
por: Wu, Minghong, et al.
Publicado: (2025)

FUSION: Forecast-Embedded Agent Scheduling with Service Incentive Optimization over Distributed Air-Ground Edge Networks
por: Qi, Houyi, et al.
Publicado: (2025)

Long-Term or Temporary? Hybrid Worker Recruitment for Mobile Crowd Sensing and Computing
por: Liwang, Minghui, et al.
Publicado: (2022)

Seamless Graph Task Scheduling over Dynamic Vehicular Clouds: A Hybrid Methodology for Integrating Pilot and Instantaneous Decisions
por: Guo, Bingshuo, et al.
Publicado: (2025)

Future Resource Bank for ISAC: Achieving Fast and Stable Win-Win Matching for Both Individuals and Coalitions
por: Qi, Houyi, et al.
Publicado: (2025)

Look One Step Ahead: Forward-Looking Incentive Design with Strategic Privacy for Proactive Service Provisioning over Air-Ground Integrated Edge Networks
por: Wu, Sicheng, et al.
Publicado: (2026)

Accelerating the Delivery of Data Services over Uncertain Mobile Crowdsensing Networks
por: Liwang, Minghui, et al.
Publicado: (2022)

Hierarchical Federated Foundation Models over Wireless Networks for Multi-Modal Multi-Task Intelligence: Integration of Edge Learning with D2D/P2P-Enabled Fog Learning Architectures
por: Abdisarabshali, Payam, et al.
Publicado: (2025)

Multi-Modal Multi-Task (M3T) Federated Foundation Models for Embodied AI: Potentials and Challenges for Edge Integration
por: Borazjani, Kasra, et al.
Publicado: (2025)

Game-Theoretic Safe Multi-Agent Motion Planning with Reachability Analysis for Dynamic and Uncertain Environments (Extended Version)
por: Mai, Wenbin, et al.
Publicado: (2025)

Auctioning Future Services in Edge Networks with Moving Vehicles: N-Step Look-Ahead Contracts for Sustainable Resource Provision
por: Ling, Ziqi, et al.
Publicado: (2025)

Graph Theory Meets Federated Learning over Satellite Constellations: Spanning Aggregations, Network Formation, and Performance Optimization
por: Nadimi, Fardis, et al.
Publicado: (2025)

Oh-Trust: Overbooking and Hybrid Trading-empowered Resource Scheduling with Smart Reputation Update over Dynamic Edge Networks
por: Qi, Houyi, et al.
Publicado: (2025)

Unsupervised Federated Optimization at the Edge: D2D-Enabled Learning without Labels
por: Wagle, Satyavrat, et al.
Publicado: (2024)

Multi-Modal Federated Learning for Cancer Staging over Non-IID Datasets with Unbalanced Modalities
por: Borazjani, Kasra, et al.
Publicado: (2024)

RE-MCDF: Closed-Loop Multi-Expert LLM Reasoning for Knowledge-Grounded Clinical Diagnosis
por: Shen, Shaowei, et al.
Publicado: (2026)

Device Sampling and Resource Optimization for Federated Learning in Cooperative Edge Networks
por: Wang, Su, et al.
Publicado: (2023)

Sporadic Gradient Tracking over Directed Graphs: A Theoretical Perspective on Decentralized Federated Learning
por: Zehtabi, Shahryar, et al.
Publicado: (2026)

Multi-Source to Multi-Target Decentralized Federated Domain Adaptation
por: Wang, Su, et al.
Publicado: (2023)

Resource-Constrained Decentralized Federated Learning via Personalized Event-Triggering
por: Zehtabi, Shahryar, et al.
Publicado: (2022)

Safe Multi-Agent Deep Reinforcement Learning for Privacy-Aware Edge-Device Collaborative DNN Inference
por: Wang, Hong, et al.
Publicado: (2026)

Asynchronous Multi-Model Dynamic Federated Learning over Wireless Networks: Theory, Modeling, and Optimization
por: Chang, Zhan-Lun, et al.
Publicado: (2023)

Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR
por: Nadimi, Fardis, et al.
Publicado: (2025)

Elastic Federated Learning over Open Radio Access Network (O-RAN) for Concurrent Execution of Multiple Distributed Learning Tasks
por: Abdisarabshali, Payam, et al.
Publicado: (2023)

Bridge the Present and Future: A Cross-Layer Matching Game in Dynamic Cloud-Aided Mobile Edge Networks
por: Qi, Houyi, et al.
Publicado: (2023)

From Federated Learning to X-Learning: Breaking the Barriers of Decentrality Through Random Walks
por: Salihovic, Allan, et al.
Publicado: (2025)

Risk-Budgeted Online Scheduling for Continuous Edge Inference over Evolving Time Horizons
por: Qi, Houyi, et al.
Publicado: (2026)

Privacy-Aware Joint DNN Model Deployment and Partitioning Optimization for Collaborative Edge Inference Services
por: Cheng, Zhipeng, et al.
Publicado: (2025)

The Transition from Centralized Machine Learning to Federated Learning for Mental Health in Education: A Survey of Current Methods and Future Directions
por: Ebrahimi, Maryam, et al.
Publicado: (2025)

Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels to Embeddings for Task-Specific Data Distributions
por: Borazjani, Kasra, et al.
Publicado: (2025)

PAST: Pilot and Adaptive Orchestration for Timely and Resilient Service Delivery in Edge-Assisted UAV Networks under Spatio-Temporal Dynamics
por: Qi, Houyi, et al.
Publicado: (2025)

Dynamic D2D-Assisted Federated Learning over O-RAN: Performance Analysis, MAC Scheduler, and Asymmetric User Selection
por: Abdisarabshali, Payam, et al.
Publicado: (2024)

Unlocking the Potential of Model Calibration in Federated Learning
por: Chu, Yun-Wei, et al.
Publicado: (2024)

Self-Play Enhancement via Advantage-Weighted Refinement in Online Federated LLM Fine-Tuning with Real-Time Feedback
por: Lee, Seohyun, et al.
Publicado: (2026)

Privacy-Preserving Distributed Link Predictions Among Peers in Online Classrooms Using Federated Learning
por: Hridi, Anurata Prabha, et al.
Publicado: (2025)

Federated Foundation Models in Harsh Wireless Environments: Prospects, Challenges, and Future Directions
por: Chen, Evan, et al.
Publicado: (2025)

Bringing Multi-Modal Multi-Task Federated Foundation Models to Education Domain: Prospects and Challenges
por: Borazjani, Kasra, et al.
Publicado: (2025)

Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks
por: Chu, Yun-Wei, et al.
Publicado: (2024)