Cover Image

FedSEA-LLaMA: A Secure, Efficient and Adaptive Federated Splitting Framework for Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Zishuai, zhang, Hainan, Li, Weihua, zhang, Qinnan, Dong, jin, Tong, Yongxin, Zheng, Zhiming
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources -- A Case Study on Federated Fine-tuning of LLaMA 2
by: Li, Zilinghan, et al.
Published: (2024)

EcoFed: Efficient Communication for DNN Partitioning-based Federated Learning
by: Wu, Di, et al.
Published: (2023)

FedCod: An Efficient Communication Protocol for Cross-Silo Federated Learning with Coding
by: Yan, Peishen, et al.
Published: (2024)

FedQuad: Adaptive Layer-wise LoRA Deployment and Activation Quantization for Federated Fine-Tuning
by: Li, Rukuo, et al.
Published: (2025)

FedADAS: Communication-Efficient Federated Distillation for On-Device Driver Yawn Recognition in Vehicular Networks
by: Mujtaba, Ahmed, et al.
Published: (2026)

Managing Federated Learning on Decentralized Infrastructures as a Reputation-based Collaborative Workflow
by: Wang, Yuandou, et al.
Published: (2025)

Communication-and-Computation Efficient Split Federated Learning: Gradient Aggregation and Resource Management
by: Liang, Yipeng, et al.
Published: (2025)

Split Federated Learning Empowered Vehicular Edge Intelligence: Concept, Adaptive Design and Future Directions
by: Qiang, Xianke, et al.
Published: (2024)

FedFQ: Federated Learning with Fine-Grained Quantization
by: Li, Haowei, et al.
Published: (2024)

On Resilient and Efficient Linear Secure Aggregation in Hierarchical Federated Learning
by: Weng, Shudi, et al.
Published: (2026)

FedAPTA: Federated Multi-task Learning for Heterogeneous Devices with Adaptive Layer-wise Pruning and Task-aware Aggregation
by: Yu, Zhen, et al.
Published: (2025)

Memory-Efficient Split Federated Learning for LLM Fine-Tuning on Heterogeneous Mobile Devices
by: Chen, Xiaopei, et al.
Published: (2025)

FedOptimus: Optimizing Vertical Federated Learning for Scalability and Efficiency
by: Shrivastava, Nikita, et al.
Published: (2025)

FedAgg: Adaptive Federated Learning with Aggregated Gradients
by: Yuan, Wenhao, et al.
Published: (2023)

FedFog: Resource-Aware Federated Learning in Edge and Fog Networks
by: Sobati-M, Somayeh
Published: (2025)

FedCostAware: Enabling Cost-Aware Federated Learning on the Cloud
by: Sinha, Aditya, et al.
Published: (2025)

pMixFed: Efficient Personalized Federated Learning through Adaptive Layer-Wise Mixup
by: Saadati, Yasaman, et al.
Published: (2025)

Efficient and Secure Sleepy Model for BFT Consensus
by: Ren, Pengkun, et al.
Published: (2025)

FedCDC: A Collaborative Framework for Data Consumers in Federated Learning Market
by: Shi, Zhuan, et al.
Published: (2025)

FedHC: A Hierarchical Clustered Federated Learning Framework for Satellite Networks
by: Liu, Zhuocheng, et al.
Published: (2025)

FedSZ: Leveraging Error-Bounded Lossy Compression for Federated Learning Communications
by: Wilkins, Grant, et al.
Published: (2023)

Energy-Efficient Wireless Federated Learning via Doubly Adaptive Quantization
by: Han, Xuefeng, et al.
Published: (2024)

FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching
by: Yan, Qifan, et al.
Published: (2025)

SplitFT: An Adaptive Federated Split Learning System For LLMs Fine-Tuning
by: Shan, Yimeng, et al.
Published: (2026)

FedSem: A Resource Allocation Scheme for Federated Learning Assisted Semantic Communication
by: Zhou, Xinyu, et al.
Published: (2025)

Enhancing Split Learning with Sharded and Blockchain-Enabled SplitFed Approaches
by: Sokhankhosh, Amirreza, et al.
Published: (2025)

Decentralized Proactive Model Offloading and Resource Allocation for Split and Federated Learning
by: Huang, Binbin, et al.
Published: (2024)

EnFed: An Energy-aware Federated Learning in Resource Constrained Environments for Human Activity Recognition
by: Mukherjee, Anwesha, et al.
Published: (2024)

FedCache: A Knowledge Cache-driven Federated Learning Architecture for Personalized Edge Intelligence
by: Wu, Zhiyuan, et al.
Published: (2023)

FedHFT: Efficient Federated Finetuning with Heterogeneous Edge Clients
by: Ilhan, Fatih, et al.
Published: (2025)

Asynchronous Secure Federated Learning with Byzantine aggregators
by: Del Pozzo, Antonella, et al.
Published: (2026)

Air-FedGA: A Grouping Asynchronous Federated Learning Mechanism Exploiting Over-the-air Computation
by: Ma, Qianpiao, et al.
Published: (2025)

Collaborative Satellite Computing through Adaptive DNN Task Splitting and Offloading
by: Peng, Shifeng, et al.
Published: (2024)

FedCAda: Adaptive Client-Side Optimization for Accelerated and Stable Federated Learning
by: Zhou, Liuzhi, et al.
Published: (2024)

FedBAT: Communication-Efficient Federated Learning via Learnable Binarization
by: Li, Shiwei, et al.
Published: (2024)

SuperSFL: Resource-Heterogeneous Federated Split Learning with Weight-Sharing Super-Networks
by: Asif, Abdullah Al, et al.
Published: (2026)

ParallelSFL: A Novel Split Federated Learning Framework Tackling Heterogeneity Issues
by: Liao, Yunming, et al.
Published: (2024)

FedShield-LLM: A Secure and Scalable Federated Fine-Tuned Large Language Model
by: Mia, Md Jueal, et al.
Published: (2025)

FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems
by: Li, Li, et al.
Published: (2021)

Federated k-Core Decomposition: A Secure Distributed Approach
by: Guo, Bin, et al.
Published: (2024)