Quantization

ICLR 2025arXiv:2411.05007

#2

SVDQuant: Absorbing Outliers by Low-Rank Component for 4-Bit Diffusion Models

Muyang Li, Yujun Lin, Zhekai Zhang et al.

model quantizationdiffusion modelslow-rank approximationsingular value decomposition+4

90

AAAI 2024arXiv:2212.01593

#3

Make RepVGG Greater Again: A Quantization-Aware Approach

Xuesong Nie, Yunfeng Yan, Siyuan Li et al.

architecture reparameterizationquantization errorint8 inferencepost-training quantization+4

65

ICLR 2025arXiv:2411.04330

#4

Scaling Laws for Precision

Tanishq Kumar, Zachary Ankner, Benjamin Spector et al.

low precision trainingpost-training quantizationprecision-aware scaling lawseffective parameter count+4

65

ICLR 2024arXiv:2403.12544

#5

AffineQuant: Affine Transformation Quantization for Large Language Models

Yuexiao Ma, Huixia Li, Xiawu Zheng et al.

43

ECCV 2024arXiv:2405.17873

#6

MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization

Zhao Tianchen, Xuefei Ning, Tongcheng Fang et al.

text-to-image diffusionmixed precision quantizationmemory-efficient inferencefew-step diffusion models+4

36

ICML 2025arXiv:2410.09426

#7

FlatQuant: Flatness Matters for LLM Quantization

Yuxuan Sun, Ruikang Liu, Haoli Bai et al.

29

NEURIPS 2025arXiv:2502.02631

#8

ParetoQ: Improving Scaling Laws in Extremely Low-bit LLM Quantization

Zechun Liu, Changsheng Zhao, Hanxian Huang et al.

23

CVPR 2025arXiv:2411.13918

#9

Quantization without Tears

Minghao Fu, Hao Yu, Jie Shao et al.

network quantizationmodel compressioninference accelerationweight discretization+4

14

ECCV 2024arXiv:2407.03917

#10

Timestep-Aware Correction for Quantized Diffusion Models

Yuzhe YAO, Feng Tian, Jun Chen et al.

11

ICLR 2025arXiv:2410.06040

#11

PTMQ: Post-training Multi-Bit Quantization of Neural Networks

Ke Xu, Zhongcheng Li, Shanshan Wang et al.

QERA: an Analytical Framework for Quantization Error Reconstruction

Cheng Zhang, Jeffrey T. H. Wong, Can Xiao et al.

quantization error reconstructionlow-rank approximationparameter-efficient fine-tuninglow-precision inference+4

8

ICLR 2024arXiv:2401.14110

#13

Scaling Laws for Floating–Point Quantization Training

Xingwu Sun, Shuaipeng Li, Ruobing Xie et al.

Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators

Yaniv Blumenfeld, Itay Hubara, Daniel Soudry

5

CVPR 2025arXiv:2505.21591

#15

Pioneering 4-Bit FP Quantization for Diffusion Models: Mixup-Sign Quantization and Timestep-Aware Fine-Tuning

Maosen Zhao, Pengtao Chen, Chong Yu et al.

model quantizationfloating-point quantizationdiffusion modelslow-bit quantization+4

3

ECCV 2024arXiv:2407.12637

#16

Toward INT4 Fixed-Point Training via Exploring Quantization Error for Gradients

Dohyung Kim, Junghyup Lee, Jeimin Jeon et al.

network quantizationfixed-point traininggradient quantizationquantization error analysis+4

2

low-bit quantizationsuper resolution networksedge detectionfinite-difference approximations+4

#17

Towards Robust Full Low-bit Quantization of Super Resolution Networks

Denis Makhov, Irina Zhelavskaya, Ruslan Ostapets et al.

ECCV 2024

1

ICCV 2025arXiv:2402.03666

#18

QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning

Haoxuan Wang, Yuzhang Shang, Zhihang Yuan et al.

NEURIPS 2025arXiv:2509.20214

#19

Q-Palette: Fractional-Bit Quantizers Toward Optimal Bit Allocation for Efficient LLM Deployment

DEOKJAE LEE, Hyun Oh Song

weight-only quantizationpost-training quantizationlarge language model deploymentfractional-bit quantizers+4

NEURIPS 2025arXiv:2510.20348

#20

AccuQuant: Simulating Multiple Denoising Steps for Quantizing Diffusion Models

Seunghoon Lee, Jeongwoo Choi, Byunggwan Son et al.

AAAI 2025arXiv:2412.11549

#21

MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models

Weilun Feng, Haotong Qin, Chuanguang Yang et al.

ICML 2025arXiv:2405.14917

#22

SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models

Wei Huang, Haotong Qin, Yangdong Liu et al.

ICML 2024arXiv:2403.06082

#23

FrameQuant: Flexible Low-Bit Quantization for Transformers

Harshavardhan Adepu, Zhanpeng Zeng, Li Zhang et al.

low-bit quantizationtransformer modelspost-training quantizationfusion frames+4

ICML 2024arXiv:2401.10432

#24

A2Q+: Improving Accumulator-Aware Weight Quantization

Ian Colbert, Alessandro Pappalardo, Jakoba Petri-Koenig et al.

weight quantizationaccumulator-aware quantizationneural network inferencehardware efficiency+3

ICML 2025arXiv:2412.04180

#25

SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization

Runsheng Bai, Bo Liu, qiang liu

AAAI 2024arXiv:2309.02784

#26

Understanding the Unfairness in Network Quantization

Bing Liu, wenjun Miao, Boyu Zhang et al.

Norm Tweaking: High-Performance Low-Bit Quantization of Large Language Models

Liang Li, Qingyuan Li, Bo Zhang et al.

ICML 2025arXiv:2412.14363

#28

Data-Free Quantization via Pseudo-label Filtering

Chunxiao Fan, Ziqi Wang, Dan Guo et al.

ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals

Utkarsh Saxena, Sayeh Sharify, Kaushik Roy et al.

CVPR 2024arXiv:2401.01543

#30

Retraining-Free Model Quantization via One-Shot Weight-Coupling Learning

Chen Tang, Yuan Meng, Jiacheng Jiang et al.

NEURIPS 2025arXiv:2506.13771

#31

Memory-Efficient Generative Models via Product Quantization

Jie Shao, Hanxiao Zhang, Hao Yu et al.

LittleBit: Ultra Low-Bit Quantization via Latent Factorization

Banseok Lee, Dongkyu Kim, Youngcheon You et al.

ICCV 2025arXiv:2507.22349

#33

Allowing Oscillation Quantization: Overcoming Solution Space Limitation in Low Bit-Width Quantization

Weiying Xie, Zihan Meng, Jitao Ma et al.

MSQ: Memory-Efficient Bit Sparsification Quantization

Seokho Han, Seoyeon Yoon, Jinhee Kim et al.

AAAI 2025arXiv:2403.16883

#35

GLAD: Improving Latent Graph Generative Modeling with Simple Quantization

Van Khoa Nguyen, Yoann Boget, Frantzeska Lavda et al.

ICLR 2025arXiv:2312.07950

#36

CBQ: Cross-Block Quantization for Large Language Models

Xin Ding, Xiaoyu Liu, Zhijun Tu et al.

ICCV 2025arXiv:2507.12933

#37

DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization

Dongyeun Lee, jiwan hur, Hyounguk Shon et al.

diffusion modelspost-training quantizationlow-bit quantizationchannel-wise scaling+4

NEURIPS 2025arXiv:2510.18650

#38

Binary Quadratic Quantization: Beyond First-Order Quantization for Real-Valued Matrix Compression

Kyo Kuroki, Yasuyuki Okoshi, Thiem Van Chu et al.

matrix quantizationbinary quadratic quantizationpost-training quantizationvision transformer models+4

ICML 2025arXiv:2501.17116

#39

Optimizing Large Language Model Training Using FP4 Quantization

Ruizhe Wang, Yeyun Gong, Xiao Liu et al.

AAAI 2025arXiv:2408.08554

#40

ABQ-LLM: Arbitrary-Bit Quantized Inference Acceleration for Large Language Models

Chao Zeng, Songwei Liu, Yusheng Xie et al.

low-bit integer trainingmixed-precision quantizationquantization sensitivity measurementimage classification+4

#41

Qua2SeDiMo: Quantifiable Quantization Sensitivity of Diffusion Models

Keith G. Mills, Mohammad Salameh, Ruichen Chen et al.

AMPA: Adaptive Mixed Precision Allocation for Low-Bit Integer Training

Li Ding, Wen Fei, Yuyang Huang et al.

ICML 2024

AAAI 2025arXiv:2406.03482

#43

QJL: 1-Bit Quantized JL Transform for KV Cache Quantization with Zero Overhead

Amir Zandieh, Majid Daliri, Insu Han

ICML 2025arXiv:2502.06786

#44

Matryoshka Quantization

Pranav Nair, Puranjay Datta, Jeff Dean et al.

block floating-pointlarge language modelsmodel quantizationhardware efficiency+3

#45

BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization

Lancheng Zou, Wenqian Zhao, Shuo Yin et al.

ICML 2024

CVPR 2024arXiv:2404.00103

#46

PikeLPN: Mitigating Overlooked Inefficiencies of Low-Precision Neural Networks

Marina Neseem, Conor McCullough, Randy Hsin et al.

ICML 2024arXiv:2402.04396

#47

QuIP$\#$: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks

Albert Tseng, Jerry Chee, Qingyao Sun et al.

post-training quantizationweight-only quantizationhadamard transformvector quantization+4

QuantizationReasoningLarge Language modelsAccuracy

#48

Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models

Ruikang Liu, Yuxuan Sun, Manyi Zhang et al.

COLM 2025

QuantizationMixed PrecisionInterpretability

#49

Task-Circuit Quantization: Leveraging Knowledge Localization and Interpretability for Compression

Hanqi Xiao, Yi-Lin Sung, Elias Stengel-Eskin et al.

COLM 2025

LLM QuantizationLLM CompressionPost Training Quantization

#50

ICQuant: Index Coding enables Low-bit LLM Quantization

Xinlin Li, Osama Hanna, Christina Fragouli et al.

COLM 2025