Neural Network Quantization

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36 papers in the last four weeks, up 125% on the four weeks before. 0.4% of all new papers.

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Selective Coupling of Decoupled Informative Regions: Masked Attention Alignment for Data-Free Quantization of Vision Transformers
Jun 3, 2026Biao Qian, Yang Wang, Yong Wu +1Vision Transformer Synthetic Data Generation
Department of Automation, Tsinghua University, China. · School of Computer Science and Information Engineering, Hefei University of Technology, China. · Li Auto, China.
P-Cast Precision in FP8 Attention: Sink-Induced Collapse and the Optimality of S=2^8
Jun 2, 2026Reed LauSoftmax Attention Attention Sinks
Tencent
KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks
Jun 2, 2026Lorenz K. Muller, Philippe Bich, Chiara Boretti +3LLM Quantization KV Caching
Huawei
LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection
Jun 2, 2026Liulu He, XuanAng Liu, Juntao Liu +8LLM Quantization LLM Compression
Nanjing University, China · China Mobile Research Institute, China · Xiaomi Corporation, China +2
GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation
May 31, 2026Shihao Zhang, Rayan SaabLLM Quantization Low-Rank Adaptation
Department of Mathematics, University of California San Diego
When Is 0.1% Enough? Analyzing the Combined Effects of Dimensionality Reduction and Quantization on Text Embedding Compression
May 31, 2026Riku Kisako, Hayato Tsukagoshi, Ryohei SasanoEmbedding Compression Dimensionality Reduction
Graduate School of Informatics, Nagoya University
Boundary-Protection W8A8 HiFloat8 Quantization for Large-Scale Text-to-Video Diffusion Transformers
May 31, 2026Yiming ZhaoVideo Diffusion Models Diffusion Model Quantization
University of Chinese Academy of Sciences Beijing, China
ScaleSweep: Accurate NVFP4 Post-Training Quantization of LLMs via Block Scale Initialization
May 30, 2026Li Lin, Xiaojun WanLLM Quantization 4-Bit Quantization
Wangxuan Institute of Computer Technology, Peking University
ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression
May 30, 2026Wenya Yu, Chao Zhang, Li Wang +2LLM Quantization Post-Training Quantization
School of Mathematics and Statistics, Central South University, Changsha, China · Department of Computer Science, Central South University, Changsha, China · CRAN, Université de Lorraine, CNRS, Nancy, France +1
Inner Product Aware Quantization: Provably Fast, Accurate, and Adaptive Algorithms
May 29, 2026Nathan White, Krish SingalVector Quantization Neural Network Quantization
University of Pennsylvania
HARP: Hadamard-Preconditioned Adaptive Rotation Processor for Extreme LLM Quantization
May 28, 2026Artur Zagitov, Gleb Molodtsov, Aleksandr BeznosikovLLM Quantization Rotation-Based Quantization
1MIRAI · 2BRAIn Lab · 3Innopolis University
LFQ: Logit-aware Final-block Quantization for Boosting the Generation Quality of Low-Bit Quantized LLMs
May 28, 2026Jung Hyun Lee, June Yong Yang, Jungwook Choi +1LLM Quantization Weight-Only Quantization
Kim Jaechul Graduate School of AI, KAIST, Daejeon, South Korea · LG AI Research, Seoul, South Korea · Hanyang University, Seoul, South Korea +1
The Complexity of Verifying Feedforward Neural Networks in Quantised Settings
May 28, 2026Eric Alsmann, Martin Lange, Marco SälzerNeural Network Verification Formal Verification
University of Kassel · RPTU University Kaiserslautern-Landau
Clark Hash: Stateless Sparse Johnson-Lindenstrauss Quantization for Neural Embeddings
May 27, 2026Stanislav Kirdey, Clark Labs IncEmbedding Compression Neural Network Quantization
Clark Labs Inc.
Hurwitz Quaternion Multiplicative Quantization for KV Cache Compression
May 26, 2026Kabir Swain, Sijie Han, Daniel Karl I. Weidele +3LLM Quantization KV Caching
Massachusetts Institute of Technology, Cambridge, MA, USA · University of Toronto, Toronto, Canada · IBM Research, Cambridge, MA, USA.
Timestep-Aware SVDQuant-GPTQ for W4A4 Quantization of Wan2.2-I2V
May 26, 2026Junhao Wu, Dezhong Yao, Hai JinVideo Diffusion Models Diffusion Transformer
School of Computer Science and Technology, Huazhong University of Science and Technology Wuhan, Hubei, China 430074
WINDQuant: Weight-Informed Neural Decision-Making for Global Mixed-Precision LLM Quantization
May 26, 2026Phong Nam Huu Nguyen, Khoi M. Le, Cong-Duy T Nguyen +3Mixed-Precision Quantization LLM Quantization
CAIR, VinUniversity, Vietnam
The Rescue Effect: Spatio-Semantic Early Exit Bypasses Quantization Collapse in CLIP
May 26, 2026Kahyeon Nam, Hyesong ChoiVLM Quantization Activation Quantization
Soongsil University Seoul, Republic of Korea
GoQuant: Geometric Orthogonal Residual Projection for Multiplier-Free Power-of-Two Transformer Quantization
May 25, 2026Maoyang Xiang, Tao Luo, Bo WangLLM Quantization Efficient Neural Network Inference
Information Systems Technology and Design Singapore University of Technology and Design Singapore · Institute of High Performance Computing (IHPC) Agency for Science, Technology and Research (A*STAR) Singapore
InfoQuant: Shaping Activation Distributions for Low-Bit LLM Quantization
May 25, 2026Ke Li, Dong An, Xiaoling Zang +6LLM Quantization Activation Quantization
School of Software Technology, Zhejiang University · Ant Group · College of Computer Science and Technology, Zhejiang University of Technology +3
Influence-Inspired Spectral Rotations for Extreme Low-Bit LLM Quantization
May 24, 2026Gorgi PavlovLLM Quantization Rotation-Based Quantization
Lehigh University
MX-SAFE: Versatile Inference- and Training-Proof Microscaling Format with On-the-Fly Exponent and Mantissa Bit Allocation
May 23, 2026Dahoon Park, Jahyun Koo, Sangwoo Hwang +1Mixed-Precision Quantization AI Accelerator Inference
† School of Electrical Engineering, Korea University, South Korea · ‡ Department of Electrical Engineering and Computer Science, DGIST, South Korea
BitsMoE: Cost-Aware Bit Allocation in Spectral Space for MoE LLM Quantization
May 22, 2026Jiayu Zhao, Zihan Teng, Minhao Fan +4Mixed-Precision Quantization LLM Quantization
School of Microelectronics, University of Science and Technology of China · College of Computing and Data Science, Nanyang Technological University · School of Electrical and Electronic Engineering, Nanyang Technological University
AffectCodec: Emotion-Preserving Neural Speech Codec with Block-Diagonal Residual FSQ
May 22, 2026Zhaoyang Meng, Zhengyao Ma, Kecan Mao +2Neural Audio Codecs Neural Encoding
Beijing University of Posts and Telecommunications
GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs
May 21, 2026Jianing Deng, Song Wang, Dongwei Wang +4Mixed-Precision Quantization LLM Quantization
University of Pittsburgh · University of Central Florida · University of Arizona +1
FTerViT: Fully Ternary Vision Transformer
May 20, 2026Szymon Ruciński, Pietro Bonazzi, Engin Türetken +3Ternary Quantization Vision Transformer
CSEM, Neuchâtel, Switzerland · ETH Zürich, Zurich, Switzerland
Q-ARVD: Quantizing Autoregressive Video Diffusion Models
May 20, 2026Siao Tang, Xinyin Ma, Gongfan Fang +2Video Diffusion Models Diffusion Model Quantization
National University of Singapore · The Hong Kong Polytechnic University
MGVQ: Synergizing Multi-dimensional Sensitivity-Aware and Gradient-Hessian Fusion for Vector Quantization
May 20, 2026Zhong Wang, Zukang Xu, Xing Hu +1Mixed-Precision Quantization Vision-Language Models
Bauman Moscow State Technical University · Houmo AI
ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models
May 19, 2026Arash Akbari, Arman Akbari, Masih Eskandar +11Mixed-Precision Quantization VLM Quantization
1Northeastern University · University of Georgia · 3Cisco Systems
Decomposing MXFP4 quantization error for LLM reinforcement learning: reducible bias, recoverable deadzone, and an irreducible floor
May 19, 2026Xiaocan Li, Shiliang Wu, Zheng ShenLLM Quantization 4-Bit Quantization
Huawei Canada

Jun 3, 2026, cs.CVJ/K move · Enter open · S save

Selective Coupling of Decoupled Informative Regions: Masked Attention Alignment for Data-Free Quantization of Vision Transformers

Biao Qian, Yang Wang, Yong Wu, Jungong Han

Department of Automation, Tsinghua University, China. · School of Computer Science and Information Engineering, Hefei University of Technology, China. · Li Auto, China.

Vision Transformer Synthetic Data Generation Neural Network Quantization

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Data-Free Quantization (DFQ) addresses data security concerns by synthesizing samples, without accessing real data. It has garnered increasing attention in the context of Vision Transformers (ViTs), owing to the superiority of the self-attention mechanism compared to classical convolutional operation. However, previous DFQ arts for ViTs often suffer from a distribution mismatch between synthetic samples and input distribution expected by quantized models Q, resulting in the suboptimal performance. In this paper, we propose a novel Masked Attention Alignment approach for Data-Free Quantization of ViTs, named MaskAQ, revealing that: 1) the semantics in the self-attention mechanism is predominantly localized to a sparse subset of patches, called informative regions; 2) the informative regions dominate the mutual information between synthetic samples and Q's outputs. To these ends, we incorporate differential entropy maximum over patch similarity of synthetic samples, to decouple informative regions from noisy background. To couple with varied Q, the informative regions are selected to align full-precision models with Q via a masked attention alignment objective, thus yielding high-quality synthetic samples. Furthermore, a periodic sample refreshing strategy comes up to endow MaskAQ with the capacity to continually adapt to the evolving state of Q throughout the training process, to preserve desirable mutual information with synthetic samples. Extensive experiments verify the merits of MaskAQ over state-of-the-art approaches across multiple backbones and downstream tasks. Our code is available at https://github.com/hfutqian/MaskAQ.

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