Equivariant-Aware Structured Pruning for Efficient Edge Deployment: A Comprehensive Framework with Adaptive Fine-Tuning
Fuente:
arXiv
Saved in:
| Main Author: | Alnemari, Mohammed |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning
by: Zhang, Mingyang, et al.
Published: (2023)
by: Zhang, Mingyang, et al.
Published: (2023)
Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models
by: Shirkavand, Reza, et al.
Published: (2024)
by: Shirkavand, Reza, et al.
Published: (2024)
Advancing Compositional Awareness in CLIP with Efficient Fine-Tuning
by: Peleg, Amit, et al.
Published: (2025)
by: Peleg, Amit, et al.
Published: (2025)
Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models
by: Zhang, Xinxi, et al.
Published: (2024)
by: Zhang, Xinxi, et al.
Published: (2024)
Meta-Learning Guided Pruning for Few-Shot Plant Pathology on Edge Devices
by: Uddin, Mohammed Mudassir, et al.
Published: (2026)
by: Uddin, Mohammed Mudassir, et al.
Published: (2026)
Adaptive Sharpness-Aware Pruning for Robust Sparse Networks
by: Bair, Anna, et al.
Published: (2023)
by: Bair, Anna, et al.
Published: (2023)
Ensembling Pruned Attention Heads For Uncertainty-Aware Efficient Transformers
by: Gabetni, Firas, et al.
Published: (2025)
by: Gabetni, Firas, et al.
Published: (2025)
ASAP: Attention-Shift-Aware Pruning for Efficient LVLM Inference
by: Pathak, Surendra, et al.
Published: (2026)
by: Pathak, Surendra, et al.
Published: (2026)
AdapMTL: Adaptive Pruning Framework for Multitask Learning Model
by: Xiang, Mingcan, et al.
Published: (2024)
by: Xiang, Mingcan, et al.
Published: (2024)
TAP-ViTs: Task-Adaptive Pruning for On-Device Deployment of Vision Transformers
by: Wang, Zhibo, et al.
Published: (2026)
by: Wang, Zhibo, et al.
Published: (2026)
Domain-Aware Fine-Tuning: Enhancing Neural Network Adaptability
by: Ha, Seokhyeon, et al.
Published: (2023)
by: Ha, Seokhyeon, et al.
Published: (2023)
Structured Model Pruning for Efficient Inference in Computational Pathology
by: Adnan, Mohammed, et al.
Published: (2024)
by: Adnan, Mohammed, et al.
Published: (2024)
SegFormer Fine-Tuning with Dropout: Advancing Hair Artifact Removal in Skin Lesion Analysis
by: Saad, Asif Mohammed, et al.
Published: (2025)
by: Saad, Asif Mohammed, et al.
Published: (2025)
Efficient and Versatile Robust Fine-Tuning of Zero-shot Models
by: Kim, Sungyeon, et al.
Published: (2024)
by: Kim, Sungyeon, et al.
Published: (2024)
Structurally Prune Anything: Any Architecture, Any Framework, Any Time
by: Wang, Xun, et al.
Published: (2024)
by: Wang, Xun, et al.
Published: (2024)
Mitigating Parameter Interference in Model Merging via Sharpness-Aware Fine-Tuning
by: Lee, Yeoreum, et al.
Published: (2025)
by: Lee, Yeoreum, et al.
Published: (2025)
Fairness-Aware Fine-Tuning of Vision-Language Models for Medical Glaucoma Diagnosis
by: Gu, Zijian, et al.
Published: (2025)
by: Gu, Zijian, et al.
Published: (2025)
Contrast-Aware Calibration for Fine-Tuned CLIP: Leveraging Image-Text Alignment
by: Lv, Song-Lin, et al.
Published: (2025)
by: Lv, Song-Lin, et al.
Published: (2025)
Efficient Vision-Language Reasoning via Adaptive Token Pruning
by: Li, Xue, et al.
Published: (2025)
by: Li, Xue, et al.
Published: (2025)
CAPA: Contribution-Aware Pruning and FFN Approximation for Efficient Large Vision-Language Models
by: Jha, Samyak, et al.
Published: (2026)
by: Jha, Samyak, et al.
Published: (2026)
Efficient Fine-Tuning with Domain Adaptation for Privacy-Preserving Vision Transformer
by: Nagamori, Teru, et al.
Published: (2024)
by: Nagamori, Teru, et al.
Published: (2024)
Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey and Benchmark
by: Xin, Yi, et al.
Published: (2024)
by: Xin, Yi, et al.
Published: (2024)
Domain-Aware Fine-Tuning of Foundation Models
by: Kaplan, Ugur Ali, et al.
Published: (2024)
by: Kaplan, Ugur Ali, et al.
Published: (2024)
GD-FPS: Growth-Driven Feedforward Parameter Selection for Efficient Fine-Tuning
by: Yang, Kenneth, et al.
Published: (2025)
by: Yang, Kenneth, et al.
Published: (2025)
VARD: Efficient and Dense Fine-Tuning for Diffusion Models with Value-based RL
by: Dai, Fengyuan, et al.
Published: (2025)
by: Dai, Fengyuan, et al.
Published: (2025)
Parameter-Efficient Fine-Tuning of DINOv2 for Large-Scale Font Classification
by: Chen, Daniel, et al.
Published: (2026)
by: Chen, Daniel, et al.
Published: (2026)
Exploring Parameter-Efficient Fine-Tuning to Enable Foundation Models in Federated Learning
by: Sun, Guangyu, et al.
Published: (2022)
by: Sun, Guangyu, et al.
Published: (2022)
C-SWAP: Explainability-Aware Structured Pruning for Efficient Neural Networks Compression
by: Bauvin, Baptiste, et al.
Published: (2025)
by: Bauvin, Baptiste, et al.
Published: (2025)
CoreMatching: A Co-adaptive Sparse Inference Framework with Token and Neuron Pruning for Comprehensive Acceleration of Vision-Language Models
by: Wang, Qinsi, et al.
Published: (2025)
by: Wang, Qinsi, et al.
Published: (2025)
LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning
by: Zhang, Jifan, et al.
Published: (2023)
by: Zhang, Jifan, et al.
Published: (2023)
AdaDeDup: Adaptive Hybrid Data Pruning for Efficient Large-Scale Object Detection Training
by: Kang, Feiyang, et al.
Published: (2025)
by: Kang, Feiyang, et al.
Published: (2025)
On the Robustness Tradeoff in Fine-Tuning
by: Li, Kunyang, et al.
Published: (2025)
by: Li, Kunyang, et al.
Published: (2025)
ICE-Pruning: An Iterative Cost-Efficient Pruning Pipeline for Deep Neural Networks
by: Hu, Wenhao, et al.
Published: (2025)
by: Hu, Wenhao, et al.
Published: (2025)
PruneFuse: Efficient Data Selection via Weight Pruning and Network Fusion
by: Kousar, Humaira, et al.
Published: (2026)
by: Kousar, Humaira, et al.
Published: (2026)
On-Demand Multi-Task Sparsity for Efficient Large-Model Deployment on Edge Devices
by: Huang, Lianming, et al.
Published: (2025)
by: Huang, Lianming, et al.
Published: (2025)
When Is Rank-1 Enough? Geometry-Guided Initialization for Parameter-Efficient Fine-Tuning
by: Zhao, Haoran, et al.
Published: (2026)
by: Zhao, Haoran, et al.
Published: (2026)
Enhancing Parameter-Efficient Fine-Tuning of Vision Transformers through Frequency-Based Adaptation
by: Ly, Son Thai, et al.
Published: (2024)
by: Ly, Son Thai, et al.
Published: (2024)
DoMIX: An Efficient Framework for Exploiting Domain Knowledge in Fine-Tuning
by: Kim, Dohoon, et al.
Published: (2025)
by: Kim, Dohoon, et al.
Published: (2025)
Adapt, But Don't Forget: Fine-Tuning and Contrastive Routing for Lane Detection under Distribution Shift
by: Khan, Mohammed Abdul Hafeez, et al.
Published: (2025)
by: Khan, Mohammed Abdul Hafeez, et al.
Published: (2025)
LL-ViT: Edge Deployable Vision Transformers with Look Up Table Neurons
by: Nag, Shashank, et al.
Published: (2025)
by: Nag, Shashank, et al.
Published: (2025)
Similar Items
-
LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning
by: Zhang, Mingyang, et al.
Published: (2023) -
Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models
by: Shirkavand, Reza, et al.
Published: (2024) -
Advancing Compositional Awareness in CLIP with Efficient Fine-Tuning
by: Peleg, Amit, et al.
Published: (2025) -
Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models
by: Zhang, Xinxi, et al.
Published: (2024) -
Meta-Learning Guided Pruning for Few-Shot Plant Pathology on Edge Devices
by: Uddin, Mohammed Mudassir, et al.
Published: (2026)