Quantization

AAAI 2024arXiv:2212.01593

#2

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 2024arXiv:2403.12544

#3

Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers

Lei Chen, Yuan Meng, Chen Tang et al.

AffineQuant: Affine Transformation Quantization for Large Language Models

Yuexiao Ma, Huixia Li, Xiawu Zheng et al.

43

ECCV 2024arXiv:2405.17873

#5

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

Zhao Tianchen, Xuefei Ning, Tongcheng Fang et al.

36

ICML 2025arXiv:2410.09426

#6

FlatQuant: Flatness Matters for LLM Quantization

Yuxuan Sun, Ruikang Liu, Haoli Bai et al.

29

ICLR 2025arXiv:2410.06040

#7

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

Zechun Liu, Changsheng Zhao, Hanxian Huang et al.

Timestep-Aware Correction for Quantized Diffusion Models

Yuzhe YAO, Feng Tian, Jun Chen et al.

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.

8

ICLR 2024arXiv:2401.14110

#11

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

Yaniv Blumenfeld, Itay Hubara, Daniel Soudry

5

AAAI 2025arXiv:2412.16895

#12

Scaling Laws for Floating–Point Quantization Training

Xingwu Sun, Shuaipeng Li, Ruobing Xie et al.

Adaptive Dataset Quantization

Muquan Li, Dongyang Zhang, Qiang Dong et al.

3

ECCV 2024arXiv:2407.12637

#14

Enhancing Diversity for Data-free Quantization

Kai Zhao, zhihao zhuang, Miao Zhang et al.

AHCPTQ: Accurate and Hardware-Compatible Post-Training Quantization for Segment Anything Model

Wenlun Zhang, Yunshan Zhong, Shimpei Ando et al.

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

Dohyung Kim, Junghyup Lee, Jeimin Jeon et al.

2

CVPR 2025arXiv:2505.21591

#17

Outlier-Aware Post-Training Quantization for Image Super-Resolution

Hailing Wang, Jianglin Lu, Yitian Zhang et al.

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

Haoxuan Wang, Yuzhang Shang, Zhihang Yuan et al.

Moment Quantization for Video Temporal Grounding

Xiaolong Sun, Le Wang, Sanping Zhou et al.

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

ICCV 2025arXiv:2507.12933

#21

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

Dongyeun Lee, jiwan hur, Hyounguk Shon et al.

CVPR 2025arXiv:2411.13918

#22

MSQ: Memory-Efficient Bit Sparsification Quantization

Seokho Han, Seoyeon Yoon, Jinhee Kim et al.

Quantization without Tears

Minghao Fu, Hao Yu, Jie Shao et al.

network quantizationmodel compressioninference accelerationweight discretization+4

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

#24

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

Weiying Xie, Zihan Meng, Jitao Ma et al.

Memory-Efficient Generative Models via Product Quantization

Jie Shao, Hanxiao Zhang, Hao Yu et al.

Towards Robust Full Low-bit Quantization of Super Resolution Networks

Denis Makhov, Irina Zhelavskaya, Ruslan Ostapets et al.

ECCV 2024

AAAI 2024arXiv:2309.02784

#27

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

Liang Li, Qingyuan Li, Bo Zhang et al.

AAAI 2025arXiv:2406.03482

#28

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

Amir Zandieh, Majid Daliri, Insu Han

ICLR 2025arXiv:2411.05007

#29

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

AAAI 2025arXiv:2405.15025

#30

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

Weilun Feng, Haotong Qin, Chuanguang Yang et al.

Treasures in Discarded Weights for LLM Quantization

Hao Yu, Yang Zhou, Bohua Chen et al.

OAC: Output-adaptive Calibration for Accurate Post-training Quantization

Ali Edalati, Alireza Ghaffari, Mahsa Ghazvini Nejad et al.

AAAI 2025arXiv:2403.16883

#33

GLAD: Improving Latent Graph Generative Modeling with Simple Quantization

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

ICML 2024arXiv:2403.06082

#34

Data-Free Quantization via Pseudo-label Filtering

Chunxiao Fan, Ziqi Wang, Dan Guo et al.

Towards Accurate Post-training Quantization for Diffusion Models

Changyuan Wang, Ziwei Wang, Xiuwei Xu et al.

FrameQuant: Flexible Low-Bit Quantization for Transformers

Harshavardhan Adepu, Zhanpeng Zeng, Li Zhang et al.

low-bit quantizationtransformer modelspost-training quantizationfusion frames+4

weight quantizationaccumulator-aware quantizationneural network inferencehardware efficiency+3

#37

Matryoshka Quantization

Pranav Nair, Puranjay Datta, Jeff Dean et al.

Understanding the Unfairness in Network Quantization

Bing Liu, wenjun Miao, Boyu Zhang et al.

PTQ4SAM: Post-Training Quantization for Segment Anything

Chengtao Lv, Hong Chen, Jinyang Guo et al.

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

Runsheng Bai, Bo Liu, qiang liu

A2Q+: Improving Accumulator-Aware Weight Quantization

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

ICML 2024

ICML 2025arXiv:2412.14363

#42

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

Wei Huang, Haotong Qin, Yangdong Liu et al.

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

Utkarsh Saxena, Sayeh Sharify, Kaushik Roy et al.

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

#44

Optimizing Large Language Model Training Using FP4 Quantization

Ruizhe Wang, Yeyun Gong, Xiao Liu et al.

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

Li Ding, Wen Fei, Yuyang Huang et al.

ICML 2024

ICML 2024arXiv:2402.04396

#46

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

block floating-pointlarge language modelsmodel quantizationhardware efficiency+3

#47

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

Lancheng Zou, Wenqian Zhao, Shuo Yin et al.

ICML 2024

ICLR 2025arXiv:2411.04330

#48

LittleBit: Ultra Low-Bit Quantization via Latent Factorization

Banseok Lee, Dongkyu Kim, Youngcheon You et al.

AccuQuant: Simulating Multiple Denoising Steps for Quantizing Diffusion Models

Seunghoon Lee, Jeongwoo Choi, Byunggwan Son et al.

CBQ: Cross-Block Quantization for Large Language Models

Xin Ding, Xiaoyu Liu, Zhijun Tu et al.

Scaling Laws for Precision

Tanishq Kumar, Zachary Ankner, Benjamin Spector et al.

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

NeurIPS 2025arXiv:2510.18650

#52

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

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

NeurIPS 2025arXiv:2509.20214

#53

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

DEOKJAE LEE, Hyun Oh Song