Cover Image

Exploiting Adaptive Channel Pruning for Communication-Efficient Split Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tan, Jialei, Lin, Zheng, Cai, Xiangming, Zhu, Ruoxi, Fang, Zihan, Chen, Pingping, Ni, Wei
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SL-ACC: A Communication-Efficient Split Learning Framework with Adaptive Channel-wise Compression
by: Lin, Zehang, et al.
Published: (2025)

HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models
by: Lin, Zheng, et al.
Published: (2025)

Intra-DP: A High Performance Collaborative Inference System for Mobile Edge Computing
by: Sun, Zekai, et al.
Published: (2025)

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems
by: Lin, Zheng, et al.
Published: (2025)

Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models
by: Fang, Zihan, et al.
Published: (2024)

AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks
by: Lin, Zheng, et al.
Published: (2024)

Scale-Adaptive Power Flow Analysis with Local Topology Slicing and Multi-Task Graph Learning
by: Li, Yongzhe, et al.
Published: (2026)

ESFL: Efficient Split Federated Learning over Resource-Constrained Heterogeneous Wireless Devices
by: Zhu, Guangyu, et al.
Published: (2024)

Earley-Driven Dynamic Pruning for Efficient Structured Decoding
by: Sun, Xintong, et al.
Published: (2025)

Communication-Efficient Split Learning via Adaptive Feature-Wise Compression
by: Oh, Yongjeong, et al.
Published: (2023)

LEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks
by: Lin, Zheng, et al.
Published: (2025)

APS-LSTM: Exploiting Multi-Periodicity and Diverse Spatial Dependencies for Flood Forecasting
by: Feng, Jun, et al.
Published: (2024)

MaskPrune: Mask-based LLM Pruning for Layer-wise Uniform Structures
by: Qin, Jiayu, et al.
Published: (2025)

Aggregation Alignment for Federated Learning with Mixture-of-Experts under Data Heterogeneity
by: Fang, Zihan, et al.
Published: (2026)

FedMap: Iterative Magnitude-Based Pruning for Communication-Efficient Federated Learning
by: Herzog, Alexander, et al.
Published: (2024)

SplitSEE: A Splittable Self-supervised Framework for Single-Channel EEG Representation Learning
by: Kotoge, Rikuto, et al.
Published: (2024)

Heterogeneous Graph Prompt Learning via Adaptive Weight Pruning
by: Wei, Chu-Yuan, et al.
Published: (2025)

Numerical Pruning for Efficient Autoregressive Models
by: Shen, Xuan, et al.
Published: (2024)

Prompt-prompted Adaptive Structured Pruning for Efficient LLM Generation
by: Dong, Harry, et al.
Published: (2024)

SatFed: A Resource-Efficient LEO Satellite-Assisted Heterogeneous Federated Learning Framework
by: Zhang, Yuxin, et al.
Published: (2024)

RAP: Runtime Adaptive Pruning for LLM Inference
by: Liu, Huanrong, et al.
Published: (2025)

PrunePEFT: Iterative Hybrid Pruning for Parameter-Efficient Fine-tuning of LLMs
by: Yu, Tongzhou, et al.
Published: (2025)

Brain-Inspired Efficient Pruning: Exploiting Criticality in Spiking Neural Networks
by: Chen, Shuo, et al.
Published: (2023)

ASFL: An Adaptive Model Splitting and Resource Allocation Framework for Split Federated Learning
by: Meng, Chuiyang, et al.
Published: (2026)

Agent-Omit: Adaptive Context Omission for Efficient LLM Agents
by: Ning, Yansong, et al.
Published: (2026)

An Effective Information Theoretic Framework for Channel Pruning
by: Chen, Yihao, et al.
Published: (2024)

LeanK: Learnable K Cache Channel Pruning for Efficient Decoding
by: Zhang, Yike, et al.
Published: (2025)

Unbiased Dynamic Pruning for Efficient Group-Based Policy Optimization
by: Zhu, Haodong, et al.
Published: (2026)

Adaptive Computation Pruning for the Forgetting Transformer
by: Lin, Zhixuan, et al.
Published: (2025)

ATP: Adaptive Threshold Pruning for Efficient Data Encoding in Quantum Neural Networks
by: Afane, Mohamed, et al.
Published: (2025)

Learning to Communicate Through Implicit Communication Channels
by: Wang, Han, et al.
Published: (2024)

FastForward Pruning: Efficient LLM Pruning via Single-Step Reinforcement Learning
by: Yuan, Xin, et al.
Published: (2025)

EvoMesh: Adaptive Physical Simulation with Hierarchical Graph Evolutions
by: Deng, Huayu, et al.
Published: (2024)

Adaptive and Parallel Split Federated Learning in Vehicular Edge Computing
by: Qiang, Xianke, et al.
Published: (2024)

Communication-Efficient Federated Learning with Adaptive Compression under Dynamic Bandwidth
by: Zhuansun, Ying, et al.
Published: (2024)

Learning from Complexity: Exploring Dynamic Sample Pruning of Spatio-Temporal Training
by: Chen, Wei, et al.
Published: (2026)

CEPerFed: Communication-Efficient Personalized Federated Learning for Multi-Pulse MRI Classification
by: Li, Ludi, et al.
Published: (2025)

Learn-by-interact: A Data-Centric Framework for Self-Adaptive Agents in Realistic Environments
by: Su, Hongjin, et al.
Published: (2025)

SFPrompt: Communication-Efficient Split Federated Fine-Tuning for Large Pre-Trained Models over Resource-Limited Devices
by: Cao, Linxiao, et al.
Published: (2024)

HEAPr: Hessian-based Efficient Atomic Expert Pruning in Output Space
by: Li, Ke, et al.
Published: (2025)