Imagen de Portada

Three Birds, One Stone: Solving the Communication-Memory-Privacy Trilemma in LLM Fine-tuning Over Wireless Networks with Zeroth-Order Optimization

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Cai, Zhijie, Zheng, Yuhao, Chen, Haolong, Liu, Dongzhu, Wang, Bin, Zhu, Guangxu
Formato:	Preprint
Publicado:	2026
Materias:	Distributed, Parallel, and Cluster Computing
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

FeedSign: Robust Full-parameter Federated Fine-tuning of Large Models with Extremely Low Communication Overhead of One Bit
por: Cai, Zhijie, et al.
Publicado: (2025)

Low-Latency Federated Fine-Tuning for Large Language Models Over Wireless Networks
por: Pang, Zhiwen, et al.
Publicado: (2026)

LobRA: Multi-tenant Fine-tuning over Heterogeneous Data
por: Lin, Sheng, et al.
Publicado: (2025)

MemAscend: System Memory Optimization for SSD-Offloaded LLM Fine-Tuning
por: Liaw, Yong-Cheng, et al.
Publicado: (2025)

Efficient Long Context Fine-tuning with Chunk Flow
por: Yuan, Xiulong, et al.
Publicado: (2025)

PATSMA: Parameter Auto-tuning for Shared Memory Algorithms
por: Fernandes, Joao B., et al.
Publicado: (2024)

Analysis and Optimized CXL-Attached Memory Allocation for Long-Context LLM Fine-Tuning
por: Liaw, Yong-Cheng, et al.
Publicado: (2025)

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

AI-in-the-Loop Sensing and Communication Joint Design for Edge Intelligence
por: Cai, Zhijie, et al.
Publicado: (2025)

Communication-Efficient Distributed On-Device LLM Inference Over Wireless Networks
por: Zhang, Kai, et al.
Publicado: (2025)

Chameleon: Taming Dynamic Operator Sequences for Memory-Intensive LLM Training
por: Wang, Zibo, et al.
Publicado: (2025)

Split Fine-Tuning for Large Language Models in Wireless Networks
por: Zhang, Songge, et al.
Publicado: (2025)

Constrained Over-the-Air Model Updating for Wireless Online Federated Learning with Delayed Information
por: Wang, Juncheng, et al.
Publicado: (2025)

KS+: Predicting Workflow Task Memory Usage Over Time
por: Bader, Jonathan, et al.
Publicado: (2024)

MemFine: Memory-Aware Fine-Grained Scheduling for MoE Training
por: Zhao, Lu, et al.
Publicado: (2025)

Converge Faster, Talk Less: Hessian-Informed Federated Zeroth-Order Optimization
por: Li, Zhe, et al.
Publicado: (2025)

Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
por: Li, Zhe, et al.
Publicado: (2024)

Distributed On-Device LLM Inference With Over-the-Air Computation
por: Zhang, Kai, et al.
Publicado: (2025)

Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence
por: Ansaripour, Matin, et al.
Publicado: (2022)

Rethinking Resource Management in Edge Learning: A Joint Pre-training and Fine-tuning Design Paradigm
por: Lyu, Zhonghao, et al.
Publicado: (2024)

Heterogeneous Federated Fine-Tuning with Parallel One-Rank Adaptation
por: Zhang, Zikai, et al.
Publicado: (2026)

Parallel Order-Based Core Maintenance in Dynamic Graphs
por: Guo, Bin, et al.
Publicado: (2022)

Stone Duality Proofs for Colorless Distributed Computability Theorems
por: Calk, Cameron, et al.
Publicado: (2025)

FlexSpec: Frozen Drafts Meet Evolving Targets in Edge-Cloud Collaborative LLM Speculative Decoding
por: Li, Yuchen, et al.
Publicado: (2026)

Semantic-aware Token Selection and Resource Optimization for Communication-efficient Split Federated Fine-tuning in Edge Intelligence
por: Qiang, Xianke, et al.
Publicado: (2026)

eLLM: Elastic Memory Management Framework for Efficient LLM Serving
por: Xu, Jiale, et al.
Publicado: (2025)

When Foresight Pruning Meets Zeroth-Order Optimization: Efficient Federated Learning for Low-Memory Devices
por: Zhang, Pengyu, et al.
Publicado: (2024)

Performance Trade-offs of High Order Meshless Approximation on Distributed Memory Systems
por: Vehovar, Jon, et al.
Publicado: (2025)

Shared Memory-Aware Latency-Sensitive Message Aggregation for Fine-Grained Communication
por: Chandrasekar, Kavitha, et al.
Publicado: (2024)

Jenga: Effective Memory Management for Serving LLM with Heterogeneity
por: Zhang, Chen, et al.
Publicado: (2025)

SYMPHONY: Improving Memory Management for LLM Inference Workloads
por: Agarwal, Saurabh, et al.
Publicado: (2024)

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

SplitLLM: Hierarchical Split Learning for Large Language Model over Wireless Network
por: Zhang, Songge, et al.
Publicado: (2025)

CacheFL: Privacy-Preserving and Efficient Federated Cache Model Fine-Tuning for Vision-Language Models
por: Yi, Mengjun, et al.
Publicado: (2025)

Memory-Efficient Federated Fine-Tuning of Large Language Models via Layer Pruning
por: Wu, Yebo, et al.
Publicado: (2025)

Memory-Centric Computing: Solving Computing's Memory Problem
por: Mutlu, Onur, et al.
Publicado: (2025)

DRust: Language-Guided Distributed Shared Memory with Fine Granularity, Full Transparency, and Ultra Efficiency
por: Ma, Haoran, et al.
Publicado: (2024)

LLM-Driven Intent-Based Privacy-Aware Orchestration Across the Cloud-Edge Continuum
por: Su, Zijie, et al.
Publicado: (2026)

SiDP: Memory-Efficient Data Parallelism for Offline LLM Inference
por: Zhao, Alan, et al.
Publicado: (2026)

FASER: Fine-Grained Phase Management for Speculative Decoding in Dynamic LLM Serving
por: Chen, Wenyan, et al.
Publicado: (2026)