Cover Image

Enhancing Quantization-Aware Training on Edge Devices via Relative Entropy Coreset Selection and Cascaded Layer Correction

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tong, Yujia, Yuan, Jingling, Hu, Chuang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LetheViT: Selective Machine Unlearning for Vision Transformers via Attention-Guided Contrastive Learning
by: Tong, Yujia, et al.
Published: (2025)

Efficient and Robust Quantization-aware Training via Adaptive Coreset Selection
by: Huang, Xijie, et al.
Published: (2023)

Efficient Multi-bit Quantization Network Training via Weight Bias Correction and Bit-wise Coreset Sampling
by: Kim, Jinhee, et al.
Published: (2025)

SAGE: Accelerating Vision-Language Models via Entropy-Guided Adaptive Speculative Decoding
by: Tong, Yujia, et al.
Published: (2026)

A Coreset Selection of Coreset Selection Literature: Introduction and Recent Advances
by: Moser, Brian B., et al.
Published: (2025)

DFQ-ViT: Data-Free Quantization for Vision Transformers without Fine-tuning
by: Tong, Yujia, et al.
Published: (2025)

Coreset Selection for Object Detection
by: Lee, Hojun, et al.
Published: (2024)

The Impact of Coreset Selection on Spurious Correlations and Group Robustness
by: Dharmasiri, Amaya, et al.
Published: (2025)

Enhancing Post-Training Quantization via Future Activation Awareness
by: Lv, Zheqi, et al.
Published: (2026)

Robust Machine Unlearning for Quantized Neural Networks via Adaptive Gradient Reweighting with Similar Labels
by: Tong, Yujia, et al.
Published: (2025)

The Easy Path to Robustness: Coreset Selection using Sample Hardness
by: Ramesh, Pranav, et al.
Published: (2025)

QGen: On the Ability to Generalize in Quantization Aware Training
by: AskariHemmat, MohammadHossein, et al.
Published: (2024)

Visual Attention Drifts,but Anchors Hold:Mitigating Hallucination in Multimodal Large Language Models via Cross-Layer Visual Anchors
by: Yang, Chengxu, et al.
Published: (2026)

Modular Quantization-Aware Training for 6D Object Pose Estimation
by: Javed, Saqib, et al.
Published: (2023)

Q-Drift: Quantization-Aware Drift Correction for Diffusion Model Sampling
by: Ryu, Sooyoung, et al.
Published: (2026)

Scaling Up Quantization-Aware Neural Architecture Search for Efficient Deep Learning on the Edge
by: Lu, Yao, et al.
Published: (2024)

EPTQ: Enhanced Post-Training Quantization via Hessian-guided Network-wise Optimization
by: Gordon, Ofir, et al.
Published: (2023)

Coreset selection based on Intra-class diversity
by: Ashraf, Imran, et al.
Published: (2025)

Training-Free Vector Quantization via Gaussian VAEs
by: Xu, Tongda, et al.
Published: (2025)

SEE-DPO: Self Entropy Enhanced Direct Preference Optimization
by: Shekhar, Shivanshu, et al.
Published: (2024)

TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge
by: Kwon, Young D., et al.
Published: (2023)

Enhancing Adversarial Robustness via Uncertainty-Aware Distributional Adversarial Training
by: Dong, Junhao, et al.
Published: (2024)

SOLAR: Switchable Output Layer for Accuracy and Robustness in Once-for-All Training
by: Tareen, Shaharyar Ahmed Khan, et al.
Published: (2025)

SCOPE: Semantic Coreset with Orthogonal Projection Embeddings for Federated learning
by: Hossen, Md Anwar, et al.
Published: (2026)

DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation
by: Zhang, Yunbei, et al.
Published: (2024)

EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models
by: Liu, Xuewen, et al.
Published: (2024)

Outlier-Aware Training for Low-Bit Quantization of Structural Re-Parameterized Networks
by: Niu, Muqun, et al.
Published: (2024)

Deep Model Interpretation with Limited Data : A Coreset-based Approach
by: Behzadi-Khormouji, Hamed, et al.
Published: (2024)

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training
by: Chen, Yangyi, et al.
Published: (2025)

Learning to Generate Gradients for Test-Time Adaptation via Test-Time Training Layers
by: Deng, Qi, et al.
Published: (2024)

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation
by: Vepa, Arvind Murari, et al.
Published: (2024)

Survey of Quantization Techniques for On-Device Vision-based Crack Detection
by: Zhang, Yuxuan, et al.
Published: (2025)

MGVQ: Synergizing Multi-dimensional Sensitivity-Aware and Gradient-Hessian Fusion for Vector Quantization
by: Wang, Zhong, et al.
Published: (2026)

Enhancing Vector Quantization with Distributional Matching: A Theoretical and Empirical Study
by: Fang, Xianghong, et al.
Published: (2025)

EdgeOL: Efficient in-situ Online Learning on Edge Devices
by: Li, Sheng, et al.
Published: (2024)

Quantize-then-Rectify: Efficient VQ-VAE Training
by: Zhang, Borui, et al.
Published: (2025)

Instance-Aware Group Quantization for Vision Transformers
by: Moon, Jaehyeon, et al.
Published: (2024)

Data-Augmented Quantization-Aware Knowledge Distillation
by: Kur, Justin, et al.
Published: (2025)

TMPQ-DM: Joint Timestep Reduction and Quantization Precision Selection for Efficient Diffusion Models
by: Sun, Haojun, et al.
Published: (2024)

CAST: Collapse-Aware multi-Scale Topology Fusion for Multimodal Coreset Selection
by: Zhao, Boran, et al.
Published: (2026)