Cover Image

Exploring Federated Pruning for Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Guo, Pengxin, Wang, Yinong, Li, Wei, Liu, Mengting, Li, Ming, Zheng, Jinkai, Qu, Liangqiong
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Unveiling Implicit Advantage Symmetry: Why GRPO Struggles with Exploration and Difficulty Adaptation
by: Yu, Zhiqi, et al.
Published: (2026)

FedVLMBench: Benchmarking Federated Fine-Tuning of Vision-Language Models
by: Zheng, Weiying, et al.
Published: (2025)

Selective Aggregation for Low-Rank Adaptation in Federated Learning
by: Guo, Pengxin, et al.
Published: (2024)

Tackling Data Heterogeneity in Federated Learning via Loss Decomposition
by: Zeng, Shuang, et al.
Published: (2024)

SwiftPrune: Hessian-Free Weight Pruning for Large Language Models
by: Kang, Yuhan, et al.
Published: (2025)

PAT: Pruning-Aware Tuning for Large Language Models
by: Liu, Yijiang, et al.
Published: (2024)

Symmetric Pruning of Large Language Models
by: Yi, Kai, et al.
Published: (2025)

Beware of Calibration Data for Pruning Large Language Models
by: Ji, Yixin, et al.
Published: (2024)

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
by: Chen, Zhikai, et al.
Published: (2023)

The Structural Scalpel: Automated Contiguous Layer Pruning for Large Language Models
by: Lu, Yao, et al.
Published: (2025)

SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training
by: Tang, Shengkun, et al.
Published: (2026)

Adaptive Pruning for Large Language Models with Structural Importance Awareness
by: Zheng, Haotian, et al.
Published: (2024)

Large Language Models Explore by Latent Distilling
by: Zeng, Yuanhao, et al.
Published: (2026)

Large Language Model Pruning
by: Huang, Hanjuan, et al.
Published: (2024)

GPrune-LLM: Generalization-Aware Structured Pruning for Large Language Models
by: Liu, Xiaoyun, et al.
Published: (2026)

Sink-Aware Pruning for Diffusion Language Models
by: Myrzakhan, Aidar, et al.
Published: (2026)

On the Limits of Layer Pruning for Generative Reasoning in Large Language Models
by: Shrestha, Safal, et al.
Published: (2026)

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

Integration of Large Language Models and Federated Learning
by: Chen, Chaochao, et al.
Published: (2023)

Exploring the Vulnerabilities of Federated Learning: A Deep Dive into Gradient Inversion Attacks
by: Guo, Pengxin, et al.
Published: (2025)

Generalized Category Discovery in Federated Graph Learning
by: Yuan, Zhongzheng, et al.
Published: (2026)

Evidence-based Distributional Alignment for Large Language Models
by: Pham, Viet-Thanh, et al.
Published: (2026)

IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model Pretraining
by: Li, Yixiao, et al.
Published: (2025)

From Local to Global: Revisiting Structured Pruning Paradigms for Large Language Models
by: Wang, Ziyan, et al.
Published: (2025)

LEAP: Learnable End-to-End Adaptive Pruning of Large Language Models
by: Mozaffari, Mohammad, et al.
Published: (2026)

Exploring Large Language Models for Climate Forecasting
by: Wang, Yang, et al.
Published: (2024)

MLLM-LLaVA-FL: Multimodal Large Language Model Assisted Federated Learning
by: Zhang, Jianyi, et al.
Published: (2024)

A Simple and Effective Pruning Approach for Large Language Models
by: Sun, Mingjie, et al.
Published: (2023)

Exploring Token Pruning in Vision State Space Models
by: Zhan, Zheng, et al.
Published: (2024)

A Dual Large Language Models Architecture with Herald Guided Prompts for Parallel Fine Grained Traffic Signal Control
by: Guo, Qing, et al.
Published: (2025)

Think Before You Prune: Self-Reflective Structured Pruning for Reasoning Language Models
by: Wang, Ziyan, et al.
Published: (2025)

The Curse of Depth in Large Language Models
by: Sun, Wenfang, et al.
Published: (2025)

Sample-aware Adaptive Structured Pruning for Large Language Models
by: Kong, Jun, et al.
Published: (2025)

Online Test-Time Adaptation of Spatial-Temporal Traffic Flow Forecasting
by: Guo, Pengxin, et al.
Published: (2024)

Wanda++: Pruning Large Language Models via Regional Gradients
by: Yang, Yifan, et al.
Published: (2025)

LLM-Rank: A Graph Theoretical Approach to Pruning Large Language Models
by: Hoffmann, David, et al.
Published: (2024)

Pruning Large Language Models by Identifying and Preserving Functional Networks
by: Liu, Yiheng, et al.
Published: (2025)

An Interpretable and Scalable Framework for Evaluating Large Language Models
by: Qu, Xinhao, et al.
Published: (2026)

Exploring the Potential of Large Language Models as Predictors in Dynamic Text-Attributed Graphs
by: Lei, Runlin, et al.
Published: (2025)

PPC-GPT: Federated Task-Specific Compression of Large Language Models via Pruning and Chain-of-Thought Distillation
by: Fan, Tao, et al.
Published: (2025)