Cover Image

LoRaQ: Optimized Low Rank Approximation for 4-bit Quantization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bouquet, Yann, Khodamoradi, Alireza, Shen, Sophie Yáng, Denolf, Kristof, Salzmann, Mathieu
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Error Diffusion: Post Training Quantization with Block-Scaled Number Formats for Neural Networks
by: Khodamoradi, Alireza, et al.
Published: (2024)

AdaHOP: Fast and Accurate Low-Precision Training via Outlier-Pattern-Aware Rotation
by: Kim, Seonggon, et al.
Published: (2026)

LoRIF: Low-Rank Influence Functions for Scalable Training Data Attribution
by: Li, Shuangqi, et al.
Published: (2026)

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

LoQT: Low-Rank Adapters for Quantized Pretraining
by: Loeschcke, Sebastian, et al.
Published: (2024)

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

DiRotQ: Rotation-Aware Quantization for 4-bit Diffusion Transformers
by: Sharify, Sayeh, et al.
Published: (2026)

FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation
by: Wang, Dannong, et al.
Published: (2024)

QT-DoG: Quantization-aware Training for Domain Generalization
by: Javed, Saqib, et al.
Published: (2024)

LoRA-GA: Low-Rank Adaptation with Gradient Approximation
by: Wang, Shaowen, et al.
Published: (2024)

ParetoQ: Improving Scaling Laws in Extremely Low-bit LLM Quantization
by: Liu, Zechun, et al.
Published: (2025)

Atom: Low-bit Quantization for Efficient and Accurate LLM Serving
by: Zhao, Yilong, et al.
Published: (2023)

CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs
by: Zhou, Zhaojing, et al.
Published: (2025)

LoPRo: Enhancing Low-Rank Quantization via Permuted Block-Wise Rotation
by: Gu, Hongyaoxing, et al.
Published: (2026)

MiLo: Efficient Quantized MoE Inference with Mixture of Low-Rank Compensators
by: Huang, Beichen, et al.
Published: (2025)

RILQ: Rank-Insensitive LoRA-based Quantization Error Compensation for Boosting 2-bit Large Language Model Accuracy
by: Lee, Geonho, et al.
Published: (2024)

LoRDO: Distributed Low-Rank Optimization with Infrequent Communication
by: Jovanović, Andrej, et al.
Published: (2026)

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

TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling
by: Gu, Hongyaoxing, et al.
Published: (2026)

LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search
by: Jääsaari, Elias, et al.
Published: (2024)

LoRaCompass: Robust Reinforcement Learning to Efficiently Search for a LoRa Tag
by: He, Tianlang, et al.
Published: (2025)

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization
by: Li, Zhikai, et al.
Published: (2026)

4bit-Quantization in Vector-Embedding for RAG
by: Jeong, Taehee
Published: (2025)

A Statistical Evaluation of Indoor LoRaWAN Environment-Aware Propagation for 6G: MLR, ANOVA, and Residual Distribution Analysis
by: Obiri, Nahshon Mokua, et al.
Published: (2025)

Low-bit Model Quantization for Deep Neural Networks: A Survey
by: Liu, Kai, et al.
Published: (2025)

Environment-Aware Indoor LoRaWAN Ranging Using Path Loss Model Inversion and Adaptive RSSI Filtering
by: Obiri, Nahshon Mokua, et al.
Published: (2025)

ICQuant: Index Coding enables Low-bit LLM Quantization
by: Li, Xinlin, et al.
Published: (2025)

LoaQ: Layer-wise Output Approximation Quantization
by: Lin, Li, et al.
Published: (2025)

ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals
by: Saxena, Utkarsh, et al.
Published: (2024)

Low-Rank Correction for Quantized LLMs
by: Scetbon, Meyer, et al.
Published: (2024)

A Comprehensive Data Description for LoRaWAN Path Loss Measurements in an Indoor Office Setting: Effects of Environmental Factors
by: Obiri, Nahshon Mokua, et al.
Published: (2025)

Environment-Aware Indoor LoRaWAN Path Loss: Parametric Regression Comparisons, Shadow Fading, and Calibrated Fade Margins
by: Obiri, Nahshon Mokua, et al.
Published: (2025)

AltLoRA: Towards Better Gradient Approximation in Low-Rank Adaptation with Alternating Projections
by: Yu, Xin, et al.
Published: (2025)

LoRAP: Low-Rank Aggregation Prompting for Quantized Graph Neural Networks Training
by: Liu, Chenyu, et al.
Published: (2026)

decoupleQ: Towards 2-bit Post-Training Uniform Quantization via decoupling Parameters into Integer and Floating Points
by: Guo, Yi, et al.
Published: (2024)

Weight Space Representation Learning via Neural Field Adaptation
by: Yang, Zhuoqian, et al.
Published: (2025)

Irrational Complex Rotations Empower Low-bit Optimizers
by: Tian, Zhen, et al.
Published: (2025)

MuonQ: Enhancing Low-Bit Muon Quantization via Directional Fidelity Optimization
by: Su, Yupeng, et al.
Published: (2026)

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

SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization
by: Bai, Runsheng, et al.
Published: (2024)