:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Lin, Li, Wan, Xiaojun
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2509.06297
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Layer-wise Quantization for Quantized Optimistic Dual Averaging
by: Nguyen, Anh Duc, et al.
Published: (2025)

Geometric Layer-wise Approximation Rates for Deep Networks
by: Zhang, Shijun, et al.
Published: (2026)

Exploring Layer-wise Information Effectiveness for Post-Training Quantization in Small Language Models
by: Xiao, He, et al.
Published: (2025)

LoRaQ: Optimized Low Rank Approximation for 4-bit Quantization
by: Bouquet, Yann, et al.
Published: (2026)

LAQuant: A Simple Overhead-free Large Reasoning Model Quantization by Layer-wise Lookahead Loss
by: Choi, Euntae, et al.
Published: (2026)

GlowQ: Group-Shared LOw-Rank Approximation for Quantized LLMs
by: An, Selim, et al.
Published: (2026)

Quantizer Design for Finite Model Approximations, Model Learning, and Quantized Q-Learning for MDPs with Unbounded Spaces
by: Bicer, Osman, et al.
Published: (2025)

Scalable Model Merging with Progressive Layer-wise Distillation
by: Xu, Jing, et al.
Published: (2025)

Layer-wise Linear Mode Connectivity
by: Adilova, Linara, et al.
Published: (2023)

Layer-wise Derivative Controlled Networks
by: Martnishn, Rowan, et al.
Published: (2026)

Layer-wise dynamic rank for compressing large language models
by: Mi, Zhendong, et al.
Published: (2025)

Beyond Higher Rank: Token-wise Input-Output Projections for Efficient Low-Rank Adaptation
by: Li, Shiwei, et al.
Published: (2025)

Resource-Efficient Federated Multimodal Learning via Layer-wise and Progressive Training
by: Tun, Ye Lin, et al.
Published: (2024)

LUT-KAN: Segment-wise LUT Quantization for Fast KAN Inference
by: Kuznetsov, Oleksandr
Published: (2026)

A Layer-wise Analysis of Supervised Fine-Tuning
by: Zhao, Qinghua, et al.
Published: (2026)

Resource-efficient Layer-wise Federated Self-supervised Learning
by: Tun, Ye Lin, et al.
Published: (2024)

FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking
by: Shi, Changlong, et al.
Published: (2025)

LOTOS: Layer-wise Orthogonalization for Training Robust Ensembles
by: Ebrahimpour-Boroojeny, Ali, et al.
Published: (2024)

Two-Stage Grid Optimization for Group-wise Quantization of LLMs
by: Kim, Junhan, et al.
Published: (2026)

Beyond Outliers: A Data-Free Layer-wise Mixed-Precision Quantization Approach Driven by Numerical and Structural Dual-Sensitivity
by: Zhang, Hengyuan, et al.
Published: (2026)

Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients
by: Zhang, Zhenyu, et al.
Published: (2024)

On the Effect of Uncertainty on Layer-wise Inference Dynamics
by: Kim, Sunwoo, et al.
Published: (2025)

Interpreting Attention Layer Outputs with Sparse Autoencoders
by: Kissane, Connor, et al.
Published: (2024)

DLink: Distilling Layer-wise and Dominant Knowledge from EEG Foundation Models
by: Wang, Jingyuan, et al.
Published: (2026)

ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression
by: Yu, Wneya, et al.
Published: (2026)

Rethinking Layer-wise Model Merging through Chain of Merges
by: Buzzega, Pietro, et al.
Published: (2025)

Element-wise Modulation of Random Matrices for Efficient Neural Layers
by: Szorc, Maksymilian
Published: (2025)

Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling
by: Wang, Fei, et al.
Published: (2026)

Targeted Vaccine: Safety Alignment for Large Language Models against Harmful Fine-Tuning via Layer-wise Perturbation
by: Liu, Guozhi, et al.
Published: (2024)

Misspecified $Q$-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error
by: Du, Ally Yalei, et al.
Published: (2024)

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation
by: Wu, Zhuguanyu, et al.
Published: (2025)

Layer-wise Weight Selection for Power-Efficient Neural Network Acceleration
by: Fang, Jiaxun, et al.
Published: (2025)

LoopQ: Quantization for Recursive Transformers
by: Fang, Rui, et al.
Published: (2026)

Joint Pruning and Channel-wise Mixed-Precision Quantization for Efficient Deep Neural Networks
by: Motetti, Beatrice Alessandra, et al.
Published: (2024)

Progressive Element-wise Gradient Estimation for Neural Network Quantization
by: Zhao, Kaiqi
Published: (2025)

Variational Inference on the Final-Layer Output of Neural Networks
by: Wei, Yadi, et al.
Published: (2023)

OAC: Output-adaptive Calibration for Accurate Post-training Quantization
by: Edalati, Ali, et al.
Published: (2024)

SliceGX: Layer-wise GNN Explanation with Model-slicing
by: Zhu, Tingting, et al.
Published: (2025)

SplitQuant: Layer Splitting for Low-Bit Neural Network Quantization
by: Song, Jaewoo, et al.
Published: (2025)

Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning
by: Kim, Jisoo, et al.
Published: (2025)