LNPT: Label-free Network Pruning and Training
Fuente:
arXiv
Saved in:
| Main Authors: | Xiao, Jinying, Li, Ping, Tang, Zhe, Nie, Jie |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
SEVEN: Pruning Transformer Model by Reserving Sentinels
by: Xiao, Jinying, et al.
Published: (2024)
by: Xiao, Jinying, et al.
Published: (2024)
TED: Accelerate Model Training by Internal Generalization
by: Xiao, Jinying, et al.
Published: (2024)
by: Xiao, Jinying, et al.
Published: (2024)
EMP: Enhance Memory in Data Pruning
by: Xiao, Jinying, et al.
Published: (2024)
by: Xiao, Jinying, et al.
Published: (2024)
Training-free Graph Neural Networks and the Power of Labels as Features
by: Sato, Ryoma
Published: (2024)
by: Sato, Ryoma
Published: (2024)
DuoGPT: Training-free Dual Sparsity through Activation-aware Pruning in LLMs
by: Yin, Ruokai, et al.
Published: (2025)
by: Yin, Ruokai, et al.
Published: (2025)
Concurrent Training and Layer Pruning of Deep Neural Networks
by: Guenter, Valentin Frank Ingmar, et al.
Published: (2024)
by: Guenter, Valentin Frank Ingmar, et al.
Published: (2024)
MosaicDiff: Training-free Structural Pruning for Diffusion Model Acceleration Reflecting Pretraining Dynamics
by: Guo, Bowei, et al.
Published: (2025)
by: Guo, Bowei, et al.
Published: (2025)
Quantifying Emergence in Neural Networks: Insights from Pruning and Training Dynamics
by: AlShinaifi, Faisal, et al.
Published: (2024)
by: AlShinaifi, Faisal, et al.
Published: (2024)
CoRE: Enhancing Metacognition with Label-free Self-evaluation in LRMs
by: Li, Haoxi, et al.
Published: (2025)
by: Li, Haoxi, et al.
Published: (2025)
Balanced Edge Pruning for Graph Anomaly Detection with Noisy Labels
by: Wang, Zhu, et al.
Published: (2024)
by: Wang, Zhu, et al.
Published: (2024)
Supervised Robustness-preserving Data-free Neural Network Pruning
by: Meng, Mark Huasong, et al.
Published: (2022)
by: Meng, Mark Huasong, et al.
Published: (2022)
Soft Label Pruning and Quantization for Large-Scale Dataset Distillation
by: Lingao, Xiao, et al.
Published: (2026)
by: Lingao, Xiao, et al.
Published: (2026)
Online Training and Pruning of Deep Reinforcement Learning Networks
by: Guenter, Valentin Frank Ingmar, et al.
Published: (2025)
by: Guenter, Valentin Frank Ingmar, et al.
Published: (2025)
Post-Training Neural Network Pruning using Graph Curvature
by: Tan, Shuhang, et al.
Published: (2026)
by: Tan, Shuhang, et al.
Published: (2026)
Training-free Heterogeneous Model Merging
by: Xu, Zhengqi, et al.
Published: (2024)
by: Xu, Zhengqi, et al.
Published: (2024)
Training-Free Dataset Pruning for Instance Segmentation
by: Dai, Yalun, et al.
Published: (2025)
by: Dai, Yalun, et al.
Published: (2025)
Hierarchical Stage-Wise Training of Linked Deep Neural Networks for Multi-Building and Multi-Floor Indoor Localization Based on Wi-Fi RSSI Fingerprinting
by: Li, Sihao, et al.
Published: (2024)
by: Li, Sihao, et al.
Published: (2024)
ResPrune: Text-Conditioned Subspace Reconstruction for Visual Token Pruning in Large Vision-Language Models
by: Li, Xu, et al.
Published: (2026)
by: Li, Xu, et al.
Published: (2026)
Variance-Based Pruning for Accelerating and Compressing Trained Networks
by: Berisha, Uranik, et al.
Published: (2025)
by: Berisha, Uranik, et al.
Published: (2025)
PAODING: A High-fidelity Data-free Pruning Toolkit for Debloating Pre-trained Neural Networks
by: Meng, Mark Huasong, et al.
Published: (2024)
by: Meng, Mark Huasong, et al.
Published: (2024)
Training-Free Restoration of Pruned Neural Networks
by: Lee, Keonho, et al.
Published: (2025)
by: Lee, Keonho, et al.
Published: (2025)
Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch
by: Wu, Xidong, et al.
Published: (2024)
by: Wu, Xidong, et al.
Published: (2024)
Explore and Establish Synergistic Effects Between Weight Pruning and Coreset Selection in Neural Network Training
by: Wan, Weilin, et al.
Published: (2025)
by: Wan, Weilin, et al.
Published: (2025)
QAdaPrune: Adaptive Parameter Pruning For Training Variational Quantum Circuits
by: Kulshrestha, Ankit, et al.
Published: (2024)
by: Kulshrestha, Ankit, et al.
Published: (2024)
PruneSymNet: A Symbolic Neural Network and Pruning Algorithm for Symbolic Regression
by: Wu, Min, et al.
Published: (2024)
by: Wu, Min, et al.
Published: (2024)
The Right to be Forgotten in Pruning: Unveil Machine Unlearning on Sparse Models
by: Xiao, Yang, et al.
Published: (2025)
by: Xiao, Yang, et al.
Published: (2025)
A Phone-based Distributed Ambient Temperature Measurement System with An Efficient Label-free Automated Training Strategy
by: Chen, Dayin, et al.
Published: (2024)
by: Chen, Dayin, et al.
Published: (2024)
Reconstruct the Pruned Model without Any Retraining
by: Wang, Pingjie, et al.
Published: (2024)
by: Wang, Pingjie, et al.
Published: (2024)
Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes
by: Zhong, Ming, et al.
Published: (2024)
by: Zhong, Ming, et al.
Published: (2024)
GraphDancer: Training LLMs to Explore and Reason over Graphs via Two-Stage Curriculum Post-Training
by: Bai, Yuyang, et al.
Published: (2026)
by: Bai, Yuyang, et al.
Published: (2026)
FASP: Fast and Accurate Structured Pruning of Large Language Models
by: Hu, Hanyu, et al.
Published: (2025)
by: Hu, Hanyu, et al.
Published: (2025)
Spectral Pruning for Recurrent Neural Networks
by: Furuya, Takashi, et al.
Published: (2021)
by: Furuya, Takashi, et al.
Published: (2021)
Rethinking Pruning for Backdoor Mitigation: An Optimization Perspective
by: Li, Nan, et al.
Published: (2024)
by: Li, Nan, et al.
Published: (2024)
Magnitude-based Neuron Pruning for Backdoor Defens
by: Li, Nan, et al.
Published: (2024)
by: Li, Nan, et al.
Published: (2024)
Fusing Pruned and Backdoored Models: Optimal Transport-based Data-free Backdoor Mitigation
by: Lin, Weilin, et al.
Published: (2024)
by: Lin, Weilin, et al.
Published: (2024)
Is Complexity Required for Neural Network Pruning? A Case Study on Global Magnitude Pruning
by: Gupta, Manas, et al.
Published: (2022)
by: Gupta, Manas, et al.
Published: (2022)
Mutual Information Preserving Neural Network Pruning
by: Westphal, Charles, et al.
Published: (2024)
by: Westphal, Charles, et al.
Published: (2024)
Pruning and Quantization Impact on Graph Neural Networks
by: Khedri, Khatoon, et al.
Published: (2025)
by: Khedri, Khatoon, et al.
Published: (2025)
A Three-regime Model of Network Pruning
by: Zhou, Yefan, et al.
Published: (2023)
by: Zhou, Yefan, et al.
Published: (2023)
Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning
by: Cao, Mingyu, et al.
Published: (2024)
by: Cao, Mingyu, et al.
Published: (2024)
Similar Items
-
SEVEN: Pruning Transformer Model by Reserving Sentinels
by: Xiao, Jinying, et al.
Published: (2024) -
TED: Accelerate Model Training by Internal Generalization
by: Xiao, Jinying, et al.
Published: (2024) -
EMP: Enhance Memory in Data Pruning
by: Xiao, Jinying, et al.
Published: (2024) -
Training-free Graph Neural Networks and the Power of Labels as Features
by: Sato, Ryoma
Published: (2024) -
DuoGPT: Training-free Dual Sparsity through Activation-aware Pruning in LLMs
by: Yin, Ruokai, et al.
Published: (2025)