Cover Image

Beyond One-Way Pruning: Bidirectional Pruning-Regrowth for Extreme Accuracy-Sparsity Tradeoff

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Junchen, Sheng, Yi
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

FedPaI: Achieving Extreme Sparsity in Federated Learning via Pruning at Initialization
by: Wang, Haonan, et al.
Published: (2025)

Weight Concentration Regularization for Improving Pruning Robustness Under High Sparsity
by: Yun, Vincent-Daniel, et al.
Published: (2025)

Maximum Redundancy Pruning: A Principle-Driven Layerwise Sparsity Allocation for LLMs
by: Gao, Chang, et al.
Published: (2025)

Post-Pruning Accuracy Recovery via Data-Free Knowledge Distillation
by: Tripurwar, Chinmay, et al.
Published: (2025)

Safe Pruning LoRA: Robust Distance-Guided Pruning for Safety Alignment in Adaptation of LLMs
by: Ao, Shuang, et al.
Published: (2025)

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

Pruning Foundation Models for High Accuracy without Retraining
by: Zhao, Pu, et al.
Published: (2024)

Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization
by: Chen, Dingshuo, et al.
Published: (2024)

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

SparK: Query-Aware Unstructured Sparsity with Recoverable KV Cache Channel Pruning
by: Liao, Huanxuan, et al.
Published: (2025)

Accuracy-Constrained CNN Pruning for Efficient and Reliable EEG-Based Seizure Detection
by: K, Mounvik, et al.
Published: (2025)

BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity Allocation
by: Xu, Peng, et al.
Published: (2024)

DTMM: Deploying TinyML Models on Extremely Weak IoT Devices with Pruning
by: Han, Lixiang, et al.
Published: (2024)

Sparsest Models Elude Pruning: An Exposé of Pruning's Current Capabilities
by: Zhang, Stephen, et al.
Published: (2024)

PruneSymNet: A Symbolic Neural Network and Pruning Algorithm for Symbolic Regression
by: Wu, Min, et al.
Published: (2024)

One Shot vs. Iterative: Rethinking Pruning Strategies for Model Compression
by: Janusz, Mikołaj, et al.
Published: (2025)

LOTUS: Improving Transformer Efficiency with Sparsity Pruning and Data Lottery Tickets
by: Upadhyay, Ojasw
Published: (2024)

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

IPPRO: Importance-based Pruning with PRojective Offset for Magnitude-indifferent Structural Pruning
by: Jung, Jaeheun, et al.
Published: (2025)

Mosaic Pruning: A Hierarchical Framework for Generalizable Pruning of Mixture-of-Experts Models
by: Hu, Wentao, et al.
Published: (2025)

TopoPrune: Robust Data Pruning via Unified Latent Space Topology
by: Roy, Arjun, et al.
Published: (2026)

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

Train One Sparse Autoencoder Across Multiple Sparsity Budgets to Preserve Interpretability and Accuracy
by: Balagansky, Nikita, et al.
Published: (2025)

DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned Models
by: Deng, Wenlong, et al.
Published: (2024)

Graph Pruning for Enumeration of Minimal Unsatisfiable Subsets
by: Lymperopoulos, Panagiotis, et al.
Published: (2024)

Pruning the Way to Reliable Policies: A Multi-Objective Deep Q-Learning Approach to Critical Care
by: Shirali, Ali, et al.
Published: (2023)

EMP: Enhance Memory in Data Pruning
by: Xiao, Jinying, et al.
Published: (2024)

TRIM: Achieving Extreme Sparsity with Targeted Row-wise Iterative Metric-driven Pruning
by: Beck, Florentin, et al.
Published: (2025)

The Neural Pruning Law Hypothesis
by: Barbulescu, Eugen, et al.
Published: (2025)

StructPrune: Structured Global Pruning asymptotics with $\mathcal{O}(\sqrt{N})$ GPU Memory
by: Song, Xinyuan, et al.
Published: (2025)

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

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

Exploring Federated Pruning for Large Language Models
by: Guo, Pengxin, et al.
Published: (2025)

OPTIMA: Optimal One-shot Pruning for LLMs via Quadratic Programming Reconstruction
by: Mozaffari, Mohammad, et al.
Published: (2025)

Exchangeability in Neural Network and its Application to Dynamic Pruning
by: Pu, et al.
Published: (2025)

Rethinking Pruning for Backdoor Mitigation: An Optimization Perspective
by: Li, Nan, et al.
Published: (2024)

Magnitude-based Neuron Pruning for Backdoor Defens
by: Li, Nan, et al.
Published: (2024)

Influence Functions for Preference Dataset Pruning
by: Fein, Daniel, et al.
Published: (2025)

Severing Spurious Correlations with Data Pruning
by: Mulchandani, Varun, et al.
Published: (2025)

Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity
by: Guo, Wentao, et al.
Published: (2024)