Awesome-Model-Quantization

This repository contains low-bit quantization papers from 2020 to 2026.

Survey

arXiv 2025 Low-bit Model Quantization for Deep Neural Networks: A Survey
Claude Survey A Chinese model quantization survey from claude concerning ICLR 2026.

Papers

2026

ICLR 2026 Channel-Aware Mixed-Precision Quantization for Efficient Long-Context Inference
ICLR 2026 CodeQuant: Unified Clustering and Quantization for Enhanced Outlier Smoothing in Low-Precision Mixture-of-Experts
ICLR 2026 QeRL: Beyond Efficiency - Quantization-enhanced Reinforcement Learning for LLMs [code]
ICLR 2026 AutoQVLA: Not All Channels Are Equal in Vision-Language-Action Model's Quantization
ICLR 2026 Achieving low-bit Muon through subspace preservation and grid quantization
ICLR 2026 Shift-and-Sum Quantization for Visual Autoregressive Models
ICLR 2026 Inlier-Centric Post-Training Quantization for Object Detection Models
ICLR 2026 Efficient Quantization of Mixture-of-Experts with Theoretical Generalization Guarantees
ICLR 2026 BBQ: Boosting Quantization Entropy with Bell Box Quantization
ICLR 2026 Improving Block-Wise LLM Quantization by 4-bit Block-Wise Optimal Float (BOF4): Analysis and Variations [code]
ICLR 2026 Learning under Quantization for High-Dimensional Linear Regression
ICLR 2026 On-the-Fly Adaptation to Quantization: Configuration-Aware LoRA for Efficient Fine-Tuning of Quantized LLMs
ICLR 2026 Bridging the Gap Between Promise and Performance for FP4 Quantization [code]
ICLR 2026 KBVQ-MoE: KLT-guided SVD with Bias-Corrected Vector Quantization for MoE Large Language Models [code]
ICLR 2026 ParoQuant: Pairwise Rotation Quantization for Efficient Reasoning LLM Inference
ICLR 2026 Post-Training Quantization for Video Matting [code]
ICLR 2026 Tequila: Deadzone-free Ternary Quantization for Large Language Models [code]
ICLR 2026 Q&C: When Quantization Meets Cache in Efficient Generation
ICLR 2026 LogART: Pushing the Limit of Efficient Logarithmic Post-Training Quantization
ICLR 2026 Quant-dLLM: Post-Training Extreme Low-Bit Quantization for Diffusion Large Language Models [code]
ICLR 2026 SliderQuant: Accurate Post-Training Quantization for LLMs
ICLR 2026 AnyBCQ: Hardware Efficient Flexible Binary-Coded Quantization for Multi-Precision LLMs [code]
ICLR 2026 UniQL: Unified Quantization and Low-rank Compression for Adaptive Edge LLMs [code]
ICLR 2026 The Lattice Geometry of Neural Network Quantization: A Short Equivalence Proof of GPTQ and Babai's algorithm
ICLR 2026 DPQuant: Efficient and Private Model Training via Dynamic Quantization Scheduling
ICLR 2026 Towards Quantization-Aware Training for Ultra-Low-Bit Reasoning LLMs
ICLR 2026 A Convergence Analysis of Adaptive Optimizers under Floating-point Quantization
ICLR 2026 Training Dynamics Impact Post-Training Quantization Robustness [code]
ICLR 2026 SSDi8: Accurate and Efficient 8-bit Quantization for State Space Duality
ICLR 2026 The Geometry of LLM Quantization: GPTQ as Babai's Nearest Plane Algorithm
ICLR 2026 PTQ4ARVG: Post-Training Quantization for AutoRegressive Visual Generation Models [code]
ICLR 2026 Inlier-Centric Post-Training Quantization for Object Detection Models
ICLR 2026 QWHA: Quantization-Aware Walsh-Hadamard Adaptation for Parameter-Efficient Fine-Tuning on Large Language Models [code]
ICLR 2026 Gradient-Aligned Calibration for Post-Training Quantization of Diffusion Models
ICLR 2026 SERQ: Saliency-Aware Low-Rank Error Reconstruction for LLM Quantization
ICLR 2026 Compute-Optimal Quantization-Aware Training
ICLR 2026 PM-KVQ: Progressive Mixed-precision KV Cache Quantization for Long-CoT LLMs [code]
ICLR 2026 Optimal Brain Restoration for Joint Quantization and Sparsification of LLMs [code]
ICLR 2026 Beyond Outliers: A Study of Optimizers Under Quantization
ICLR 2026 Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization
ICLR 2026 MicroMix: Efficient Mixed-Precision Quantization with Microscaling Formats for Large Language Models [code]
ICLR 2026 TurboBoA: Faster and Exact Attention-aware Quantization without Backpropagation
ICLR 2026 DVD-Quant: Data-free Video Diffusion Transformers Quantization [code]
ICLR 2026 Beyond Uniformity: Sample and Frequency Meta Weighting for Post-Training Quantization of Diffusion Models
ICLR 2026 Rethinking Residual Errors in Compensation-based LLM Quantization
ICLR 2026 SPR²Q: Static Priority-based Rectifier Routing Quantization for Image Super-Resolution [code]
ICLR 2026 STaMP: Sequence Transformation and Mixed Precision for Low-Precision Activation Quantization
ICLR 2026 PT²-LLM: Post-Training Ternarization for Large Language Models [code]
CVPR 2026 Quant Experts: Token-aware Adaptive Error Reconstruction with Mixture of Experts for Large Vision-Language Models Quantization
CVPR 2026 Fine-Grained Post-Training Quantization for Large Vision Language Models with Quantization-Aware Integrated Gradients [code]
CVPR 2026 MASQuant: Modality-Aware Smoothing Quantization for Multimodal Large Language Models
CVPR 2026 SegQuant: A Semantics-Aware and Generalizable Quantization Framework for Diffusion Models
CVPR 2026 VLM-PTQ: Efficient Post-Training Quantization for Large Vision-Language Models
CVPR 2026 Rethinking Asymmetric Quantization: Hidden Symmetry in Vision Model Weights
CVPR 2026 Gradient Knows Best: Mixed-Precision Quantization via Gradient-Guided Bit Allocation for Super-Resolution
CVPR 2026 DeltaQuant: 4-bit Video Diffusion Models with Spatiotemporal Delta Smoothing
CVPR 2026 LS-ViT: Least-Squares Hessian Based Block Reconstruction for Low-Bit Post-Training Quantization of Vision Transformers
CVPR 2026 QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models [code]
CVPR 2026 TWEO: Transformers Without Extreme Outliers Enables FP8 Training And Quantization For Dummies
CVPR 2026 S2D: Selective Spectral Decay for Quantization-Friendly Conditioning of Neural Activations
CVPR 2026 Q-MambaIR: Accurate Quantized Mamba for Efficient Image Restoration
CVPR 2026 FraQAT: Quantization Aware Training with Fractional Bits
CVPR 2026 Sampling-Aware Quantization for Diffusion Models
CVPR 2026 D4C: Data-Free Quantization for Contrastive Language-Image Pre-Training Models [code]
CVPR 2026 CAR-SAM: Cross-Attention Reconstruction for Post-Training Quantization of the Segment Anything Model
CVPR 2026 QVGGT: Post-Training Quantized Visual Geometry Grounded Transformer
CVPR 2026 Modality-Aware Bit Allocation for Mixed-Precision Quantization of Vision-Language Models
CVPR 2026 BinaryAttention: One-Bit QK-Attention for Vision and Diffusion Transformers [code]
ICML 2026 LO-BCQ: Locally Optimal Block Clustered Quantization for 4-bit (W4A4) LLM Inference
ICML 2026 ReQAT: Achieving Full-Precision Reasoning Accuracy with 4-bit Floating-Point Quantization-Aware Training
ICML 2026 MixQuant: Pushing the Limits of Block Rotations in Post-Training Quantization
ICML 2026 S-Quant: Rethinking Weight Quantization with Seed-Based Generation
ICML 2026 BPDQ: Bit-Plane Decomposition Quantization on a Variable Grid for Large Language Models
ICML 2026 No Retraining at Edge: Efficient Resource-Aware Mixed-Precision Quantization via Federated Supernet Learning
ICML 2026 WaterSIC: Information-Theoretically (Near) Optimal Linear Layer Quantization
ICML 2026 Q-DiT4SR: Exploration of Detail-Preserving Diffusion Transformer Quantization for Real-World Image Super-Resolution
ICML 2026 High-Dimensional Learning Dynamics of Quantized Models with Straight-Through Estimator
ICML 2026 LiftQuant: Continuous Bit-Width Control for Pareto-Optimal LLM Deployment [code]
ICML 2026 Block Rotation is All You Need for MXFP4 Quantization
ICML 2026 AutoQRA: Joint Optimization of Mixed-Precision Quantization and Low-rank Adapters for Efficient LLM Fine-Tuning
ICML 2026 1-Bit Wonder: Improving QAT Performance in the Low-Bit Regime through K-Means Quantization
ICML 2026 Attn-QAT: 4-Bit Attention With Quantization-Aware Training
ICML 2026 AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs
ICML 2026 ReSpinQuant: Efficient Layer-Wise LLM Quantization via Subspace Residual Rotation Approximation
ICML 2026 NanoQuant: Efficient Sub-1-bit Quantization of Large Language Models
ICML 2026 Proteus: Lookup-Free Trellis-Coded Quantization by Lattice-Breaking Compute Codes for 2-Bit LLMs
ICML 2026 WinQ: Accelerating Quantization-Aware Training of Large Language Models around Saddle Points [code]
ICML 2026 Toward Safe Quantization-Aware Fine-tuning: Understanding and Mitigating Safety Alignment Degradation
ICML 2026 Preserve-Then-Quantize: Balancing Rank Budgets for Quantization Error Reconstruction in LLMs
ICML 2026 GSRQ: Gain-Shape Residual Quantization for Sub-1-bit KV Cache
ICML 2026 ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression
ICML 2026 STLA: Spatiotemporal Lookahead Alignment for Post-Training Quantization
ICML 2026 FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models
ICML 2026 TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling
ICML 2026 LFQ: Logit-aware Final-block Quantization for Boosting the Generation Quality of Low-Bit Quantized LLMs
ICML 2026 DLLMQuant: A Post-Training Quantization Framework Tailored for Diffusion-Based Large Language Models
ICML 2026 SHARP-Q: Spectral Hessian Alignment and Rectification for Post-training Quantization
ICML 2026 Selective Coupling of Decoupled Informative Regions: Masked Attention Alignment for Data-Free Quantization of Vision Transformers
ICML 2026 TWLA: Breaking the Barrier to W1.58A4 Post-Training Quantization for LLMs
ICML 2026 FPTQuant: Function-Preserving Transforms for LLM Quantization
ICML 2026 INT vs. FP: A Comprehensive Study of Fine-Grained Low-bit Quantization Formats [code]
ICML 2026 Unveiling the Potential of Quantization with MXFP4: Strategies for Quantization Error Reduction
ICML 2026 Scaling Law for Quantization-Aware Training
ICML 2026 Error Propagation Mechanisms and Compensation Strategies for Quantized Diffusion Models
ICML 2026 Condition Number Based Low-Bit Quantization for Image Super-Resolution [code]
ICML 2026 ECO: Quantized Training without Full-Precision Master Weights
ICML 2026 LATMiX: Learnable Affine Transformations for Microscaling Quantization of LLMs
ICML 2026 RobuQ: Pushing DiTs to W1.58A2 via Robust Activation Quantization [code]
ICML 2026 QTALE: Quantization-Robust Token-Adaptive Layer Execution for LLMs
ICML 2026 TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization
ICML 2026 NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs
ICML 2026 VEQ: Modality-Adaptive Quantization for MoE Vision-Language Models
ICML 2026 Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization [code]
ICML 2026 OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization
ICML 2026 Q-Sched: Pushing the Boundaries of Few-Step Diffusion Models with Quantization-Aware Scheduling [code]
ICML 2026 SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights [code]
ICML 2026 Dissecting Quantization Error: A Concentration-Alignment Perspective
ICML 2026 Principled SVD-based Delta Compression via Quantization Error Minimization
ICML 2026 PatternKV: Flattening KV Representation Expands Quantization Headroom
ICML 2026 GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs
ICML 2026 WUSH: Near-Optimal Adaptive Transforms for LLM Quantization [code]
ICML 2026 LC-QAT: Data-Efficient 2-Bit QAT for LLMs via Linear-Constrained Vector Quantization
ICML 2026 LSGQuant: Layer-Sensitivity Guided Quantization for One-Step Diffusion Real-World Video Super-Resolution [code]
ICML 2026 CAT-Q: Cost-efficient and Accurate Ternary Quantization for LLMs
ICML 2026 Precision-Induced Miscalibration: Understanding and Correcting Confidence Distortion in Quantized Neural Networks
ICML 2026 CoCoQuant: Breaking the Bandwidth Wall via Co-Optimized Communication and Computation Quantization
ICML 2026 RaBitQCache: Rotated Binary Quantization for KVCache in Long Context LLM Inference
ICML 2026 ImpQuant: Fine-Grained Importance-Aware Quantization for Large Vision-Language Models
ICML 2026 Absorbing Quantization Error by Deformable Noise Scheduler for Diffusion Models
ICML 2026 PsumQuant: In-line Post-training Partial Sum Quantizer for Energy Efficient NPU Inference
ICML 2026 Towards Sub-second Biological Foundation Model Infrastructure: A Quantized Consistency Diffusion Framework for Molecular Docking
ICML 2026 MixFP4: Extending NVFP4 to Mixed Micro-Format via Scale-Bit Reuse and Tensor Core Co-design
AAAI 2026 InfoQ: Mixed-Precision Quantization via Global Information Flow
AAAI 2026 BIQ: Bisection Interval Quantization for Communication-efficient Federated Learning
AAAI 2026 Bi-VLM: Binary Post-Training Quantization for Vision-Language Models
AAAI 2026 BD-Net: Has Depth-Wise Convolution Ever Been Applied in Binary Neural Networks?

2025

NeurIPS 2025 QBasicVSR: Temporal Awareness Adaptation Quantization for Video Super-Resolution
NeurIPS 2025 ParetoQ: Improving Scaling Laws in Extremely Low-bit LLM Quantization
NeurIPS 2025 Quantization Error Propagation: Revisiting Layer-Wise Post-Training Quantization
NeurIPS 2025 DartQuant: Efficient Rotational Distribution Calibration for LLM Quantization
NeurIPS 2025 Point4Bit: Post Training 4-bit Quantization for Point Cloud 3D Detection
NeurIPS 2025 Binary Quadratic Quantization: Beyond First-Order Quantization for Real-Valued Matrix Compression
NeurIPS 2025 PMQ-VE: Progressive Multi-Frame Quantization for Video Enhancement [code]
NeurIPS 2025 VETA-DiT: Variance-Equalized and Temporally Adaptive Quantization for Efficient 4-bit Diffusion Transformers
NeurIPS 2025 LoTA-QAF: Lossless Ternary Adaptation for Quantization-Aware Fine-Tuning [code]
NeurIPS 2025 LittleBit: Ultra Low-Bit Quantization via Latent Factorization
NeurIPS 2025 HBLLM: Wavelet-Enhanced High-Fidelity 1-Bit Quantization for LLMs
NeurIPS 2025 Efficient Multi-bit Quantization Network Training via Weight Bias Correction and Bit-wise Coreset Sampling
NeurIPS 2025 Efficient and Generalizable Mixed-Precision Quantization via Topological Entropy
NeurIPS 2025 QSCA: Quantization with Self-Compensating Auxiliary for Monocular Depth Estimation
NeurIPS 2025 Q-Palette: Fractional-Bit Quantizers Toward Optimal Bit Allocation for Efficient LLM Deployment
ICCV 2025 Scheduling Weight Transitions for Quantization-Aware Training [code]
ICCV 2025 Task-Specific Zero-shot Quantization-Aware Training for Object Detection [code]
ICCV 2025 OuroMamba: A Data-Free Quantization Framework for Vision Mamba
ICCV 2025 Allowing Oscillation Quantization: Overcoming Solution Space Limitation in Low Bit-Width Quantization [code]
ICCV 2025 FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization [code]
ICCV 2025 Semantic Alignment and Reinforcement for Data-Free Quantization of Vision Transformers [code]
ICCV 2025 QuantCache: Adaptive Importance-Guided Quantization with Hierarchical Latent and Layer Caching for Video Generation [code]
ICCV 2025 MixA-Q: Revisiting Activation Sparsity for Vision Transformers from a Mixed-Precision Quantization Perspective
ICCV 2025 DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization [code]
ICCV 2025 AHCPTQ: Accurate and Hardware-Compatible Post-Training Quantization for Segment Anything Model
ICCV 2025 MSQ: Memory-Efficient Bit Sparsification Quantization
ICCV 2025 QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning [code]
ICML 2025 MxMoE: Mixed-precision Quantization for MoE with Accuracy and Performance Co-Design [code]
ICML 2025 Learning from Loss Landscape: Generalizable Mixed-Precision Quantization via Adaptive Sharpness-Aware Gradient Aligning
ICML 2025 ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals [code]
ICML 2025 SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models [code]
ICML 2025 PARQ: Piecewise-Affine Regularized Quantization [code]
ICML 2025 Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models [code]
ICML 2025 LRA-QViT: Integrating Low-Rank Approximation and Quantization for Robust and Efficient Vision Transformers
ICML 2025 BoA: Attention-aware Post-training Quantization without Backpropagation
ICML 2025 MoEQuant: Enhancing Quantization for Mixture-of-Experts Large Language Models via Expert-Balanced Sampling and Affinity Guidance [code]
ICML 2025 NestQuant: nested lattice quantization for matrix products and LLMs
ICML 2025 FlatQuant: Flatness Matters for LLM Quantization [code]
ICML 2025 Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models [code]
ICML 2025 SLiM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression [code]
ICML 2025 QT-DoG: Quantization-Aware Training for Domain Generalization [code]
ICML 2025 Matryoshka Quantization
ICML 2025 Merge-Friendly Post-Training Quantization for Multi-Target Domain Adaptation [code]
ICML 2025 Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization [code]
ICML 2025 Layer-wise Quantization for Quantized Optimistic Dual Averaging
ICML 2025 Outlier-Aware Post-Training Quantization for Discrete Graph Diffusion Models
ICML 2025 BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM Inference
ICML 2025 GPTAQ: Efficient Finetuning-Free Quantization with Asymmetric Calibration [code]
ICML 2025 Optimizing Large Language Model Training Using FP4 Quantization
ICML 2025 SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization
ICML 2025 SageAttention2: Efficient Attention with Thorough Outlier Smoothing and Per-thread INT4 Quantization [code]
ICML 2025 Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers [code]
ICML 2025 GANQ: GPU-Adaptive Non-Uniform Quantization for Large Language Models [code]
ICML 2025 GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance [code]
AAAI 2025 Qua$^2$SeDiMo: Quantifiable Quantization Sensitivity of Diffusion Models [code]
AAAI 2025 Thinking in Granularity: Dynamic Quantization for Image Super-Resolution by Intriguing Multi-Granularity Clues [code]
AAAI 2025 D2-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models [code]
AAAI 2025 MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models [code]
CVPR 2025 Quantization without Tears
CVPR 2025 APHQ-ViT: Post-Training Quantization with Average Perturbation Hessian Based Reconstruction for Vision Transformer [code]
ICLR 2025 SpinQuant: LLM quantization with learned rotations [code]
ICLR 2025 LeanQuant: Accurate and Scalable Large Language Model Quantization with Loss-error-aware Grid
ICLR 2025 CBQ: Cross-Block Quantization for Large Language Models
ICLR 2025 OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting [code]
ICLR 2025 QERA: an Analytical Framework for Quantization Error Reconstruction [code]
ICLR 2025 Svdquant: Absorbing outliers by low-rank components for 4-bit diffusion models [code]
ICLR 2025 DGQ: Distribution-Aware Group Quantization for Text-to-Image Diffusion Models [code]
ICLR 2025 SynQ: Accurate Zero-shot Quantization by Synthesis-aware Fine-tuning [code]
ICLR 2025 ViDiT-Q: Efficient and accurate quantization of diffusion transformers for image and video generation [code]

2024

AAAI 2024 MetaMix: meta-state precision searcher for mixed-precision activation quantization
AAAI 2024 Norm Tweaking: High-Performance Low-Bit Quantization of Large Language Models [code]
AAAI 2024 Make RepVGG Greater Again: A Quantization-aware Approach [code]
AAAI 2024 Bi-ViT: Pushing the Limit of Vision Transformer Quantization [code]
AAAI 2024 Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge
AAAI 2024 AQ-DETR: Low-Bit Quantized Detection Transformer with Auxiliary Queries
AAAI 2024 OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models [code]
AAAI 2024 One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training
AAAI 2024 ZeroQuant-V2: Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation [code]
CVPR 2024 TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models [code]
CVPR 2024 Retraining-free Model Quantization via One-Shot Weight-Coupling Learning [code]
CVPR 2024 Enhancing Post-training Quantization Calibration through Contrastive Learning
CVPR 2024 PTQ4SAM: Post-Training Quantization for Segment Anything [code]
CVPR 2024 CL-Calib: Enhancing Post-training Quantization Calibration through Contrastive Learning
CVPR 2024 PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution [code]
CVPR 2024 Mixed-precision quantization for federated learning on resource-constrained heterogeneous devices
CVPR 2024 Instance-Aware Group Quantization for Vision Transformers
CVPR 2024 Data-Free Quantization via Pseudo-label Filtering
CVPR 2024 Reg-PTQ: Regression-specialized Post-training Quantization for Fully Quantized Object Detector
CVPR 2024 Towards Accurate Post-training Quantization for Diffusion Models [code]
ECCV 2024 CLAMP-ViT: Contrastive data-free learning for adaptive post-training quantization of vits [code]
ECCV 2024 AdaLog: Post-Training Quantization for Vision Transformers with Adaptive Logarithm Quantizer [code]
ECCV 2024 Post-training quantization with progressive calibration and activation relaxing for text-to-image diffusion models [code]
ECCV 2024 Memory-Efficient Fine-Tuning for Quantized Diffusion Model [code]
ECCV 2024 Mixdq: Memory-efficient few-step text-to-image diffusion models with metric-decoupled mixed precision quantization [code]
ECCV 2024 Timestep-aware correction for quantized diffusion models
ECCV 2024 Clamp-vit: Contrastive data-free learning for adaptive post-training quantization of vits [code]
ICLR 2024 AffineQuant: Affine Transformation Quantization for Large Language Models [code]
ICLR 2024 LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models [code]
ICLR 2024 Loftq: Lora-fine-tuning-aware quantization for large language models [code]
ICLR 2024 OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models [code]
ICLR 2024 QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Model [code]
ICML 2024 SqueezeLLM: Dense-and-Sparse Quantization [code]
ICML 2024 A2Q+: Improving Accumulator-Aware Weight Quantization
ICML 2024 Learning from students: Applying t-distributions to explore accurate and efficient formats for llms [code]
ICML 2024 LQER:Low-Rank Quantization Error Reconstruction for LLMs [code]
ICML 2024 Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization
ICML 2024 Reshape and Adapt for Output Quantization (RAOQ): Quantization-aware Training for In-memory Computing Systems
ICML 2024 ERQ: Error Reduction for Post-Training Quantization of Vision Transformers
ICML 2024 KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache [code]
ICML 2024 BiLLM: Pushing the Limit of Post-Training Quantization for LLMs [code]
ICML 2024 QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks [code]
ICML 2024 Extreme Compression of Large Language Models via Additive Quantization [code]
ICML 2024 Outlier-aware Slicing for Post-Training Quantization in Vision Transformer
ICML 2024 BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization
ICML 2024 Reshape and Adapt for Output Quantization ({RAOQ}): Quantization-aware Training for In-memory Computing Systems
NeurIPS 2024 Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers [code]
NeurIPS 2024 QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs [code]
NeurIPS 2024 2DQuant: Low-bit Post-Training Quantization for Image Super-Resolution [code]
NeurIPS 2024 MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization [code]
NeurIPS 2024 Exploiting LLM Quantization
NeurIPS 2024 Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters
NeurIPS 2024 QTIP: Quantization with Trellises and Incoherence Processing [code]
NeurIPS 2024 Generalizing CNNs to graphs with learnable neighborhood quantization [code]
NeurIPS 2024 SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training [code]
NeurIPS 2024 Optimal and Approximate Adaptive Stochastic Quantization [code]
NeurIPS 2024 BitsFusion: 1.99 bits Weight Quantization of Diffusion Model [code]
NeurIPS 2024 BiDM: Pushing the Limit of Quantization for Diffusion Models [code]
NeurIPS 2024 MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization [code]
NeurIPS 2024 DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs [code]
NeurIPS 2024 Cherry on Top: Parameter Heterogeneity and Quantization in Large Language Models
NeurIPS 2024 Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers
NeurIPS 2024 BiDM: Pushing the Limit of Quantization for Diffusion Models [code]
NeurIPS 2024 StepbaQ: Stepping backward as Correction for Quantized Diffusion Models
NeurIPS 2024 Cherry on top: Parameter heterogeneity and quantization in large language models
NeurIPS 2024 QBB: Quantization with Binary Bases for LLMs

2023

AAAI 2023 OMPQ: Orthogonal Mixed Precision Quantization [code]
AAAI 2023 Rethinking Data-Free Quantization as a Zero-Sum Game [code]
AAAI 2023 Quantized Feature Distillation for Network Quantization
AAAI 2023 Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks [code]
CVPR 2023 Boost Vision Transformer with GPU-Friendly Sparsity and Quantization
CVPR 2023 NIPQ: Noise proxy-based Integrated Pseudo-Quantization [code]
CVPR 2023 GENIE: Show Me the Data for Quantization [code]
CVPR 2023 Hard Sample Matters a Lot in Zero-Shot Quantization [code]
CVPR 2023 One-Shot Model for Mixed-Precision Quantization
CVPR 2023 PD-Quant: Post-Training Quantization based on Prediction Difference Metric [code]
CVPR 2023 Post-training Quantization on Diffusion Models [code]
CVPR 2023 Solving Oscillation Problem in Post-Training Quantization Through a Theoretical Perspective [code]
CVPR 2023 NoisyQuant: Noisy Bias-Enhanced Post-Training Activation Quantization for Vision Transformers
CVPR 2023 Adaptive Data-Free Quantization [code]
CVPR 2023 Bit-Shrinking: Limiting Instantaneous Sharpness for Improving Post-Training Quantization
CVPR 2023 Q-DETR: An Efficient Low-Bit Quantized Detection Transformer [code]
ICCV 2023 I-ViT: Integer-only Quantization for Efficient Vision Transformer Inference [code]
ICCV 2023 RepQ-ViT: Scale Reparameterization for Post-Training Quantization of Vision Transformers [code]
ICCV 2023 Causal-dfq: Causality guided data-free network quantization [code]
ICCV 2023 Q-Diffusion: Quantizing Diffusion Models [code]
ICCV 2023 Unified data-free compression: Pruning and quantization without fine-tuning
ICLR 2023 $\rm{A}^{2} Q$: Aggregation-Aware Quantization for Graph Neural Networks
ICLR 2023 GPTQ: Accurate Post-training Quantization For Generative Pre-trained Transformers [code]
ICLR 2023 PowerQuant:Automorphism Search For Non-Uniform Quantization
ICLR 2023 Block and Subword-Scaling Floating-Point (BSFP) : An Efficient Non-Uniform Quantization For Low Precision Inference
ICLR 2023 A$^{2}$Q:Aggregation-Aware Quantization For Graph Nueral Networks [code]
ICLR 2023 PowerQuant: Automorphism Search for Non-Uniform Quantization
ICML 2023 SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models [code]
ICML 2023 FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization [code]
ICML 2023 Oscillation-free Quantization for Low-bit Vision Transformers [code]
ICML 2023 Understanding INT4 Quantization for Transformer Models: Latency Speedup, Composability, and Failure Cases [code]
ICML 2023 Quantized Distributed Training of Large Models with Convergence Guarantees
NeurIPS 2023 QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution [code]
NeurIPS 2023 Q-DM: An Efficient Low-bit Quantized Diffusion Model
NeurIPS 2023 REx: Data-Free Residual Quantization Error Expansion
NeurIPS 2023 PTQD: Accurate Post-Training Quantization for Diffusion Models [code]
NeurIPS 2023 TexQ: Zero-shot Network Quantization with Texture Feature Distribution Calibration
NeurIPS 2023 PackQViT: Faster Sub-8-bit Vision Transformers via Full and Packed Quantization on the Mobile [code]
NeurIPS 2023 Intriguing Properties of Quantization at Scale
NeurIPS 2023 QLORA: Efficient Finetuning of Quantized LLMs [code]
NeurIPS 2023 Training Transformers with 4-bit Integers [code]
NeurIPS 2023 QuIP: 2-Bit Quantization of Large Language Models With Guarantees [code]
NeurIPS 2023 Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
NeurIPS 2023 Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers
NeurIPS 2023 Towards Efficient and Accurate Winograd Convolution via Full Quantization
NeurIPS 2023 Temporal Dynamic Quantization for Diffusion Models [code]
NeurIPS 2023 Pruning vs Quantization: Which is Better? [code]

2022

CVPR 2022 Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation [code]
CVPR 2022 Learnable Lookup Table for Neural Network Quantization [code]
CVPR 2022 Mr.BiQ: Post-Training Non-Uniform Quantization based on Minimizing the Reconstruction Error
CVPR 2022 Data-Free Network Compression via Parametric Non-uniform Mixed Precision Quantization
CVPR 2022 Instance-Aware Dynamic Neural Network Quantization [code]
CVPR 2022 IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization [code]
ECCV 2022 CADyQ: Content-Aware Dynamic Quantization for Image Super-Resolution
ECCV 2022 PTQ4ViT: Post-training Quantization for Vision Transformers with Twin Uniform Quantization [code]
ECCV 2022 Bitwidth-Adaptive Quantization-Aware Neural Network Training: A Meta-Learning Approach [code]
ECCV 2022 Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance [code]
ECCV 2022 Patch Similarity Aware Data-Free Quantization for Vision Transformers [code]
ECCV 2022 Fine-grained Data Distribution Alignment for Post-Training Quantization [code]
ECCV 2022 Non-Uniform Step Size Quantization for Accurate Post-Training Quantization [code]
ICLR 2022 8-bit Optimizers via Block-wise Quantization
ICLR 2022 F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization [code]
ICLR 2022 SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation [code]
ICLR 2022 QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization [code]
ICLR 2022 Toward Efficient Low-Precision Training: Data Format Optimization and Hysteresis Quantization
ICLR 2022 VC dimension of partially quantized neural networks in the overparametrized regime. [code]
ICML 2022 Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training
ICML 2022 Overcoming Oscillations in Quantization-Aware Training [code]
ICML 2022 Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training
ICML 2022 SDQ:Stochastic Differentiable Quantization with Mixed Precision
IJCAI 2022 RAPQ: Rescuing Accuracy for Power-of-Two Low-bit Post-training Quantization [code]
IJCAI 2022 MultiQuant: Training Once for Multi-bit Quantization of Neural Networks
IJCAI 2022 FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer [code]
NeurIPS 2022 Entropy-driven mixed-precision quantization for deep network design [code]
NeurIPS 2022 Towards Efficient Post-training Quantization of Pre-trained Language Models
NeurIPS 2022 Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer [code]
NeurIPS 2022 ClimbQ: Class Imbalanced Quantization Enabling Robustness on Efficient Inferences [code]
NeurIPS 2022 Redistribution of Weights and Activations for AdderNet Quantization
NeurIPS 2022 Leveraging inter-layer dependency for post-training quantization
NeurIPS 2022 ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers
NeurIPS 2022 Leveraging Inter-Layer Dependency for Post -Training Quantization

2021

AAAI 2021 Optimizing information theory based bitwise bottlenecks for efficient mixed-precision activation quantization
AAAI 2021 Distribution Adaptive INT8 Quantization for Training CNNs [code]
AAAI 2021 Stochastic Precision Ensemble: Self‐Knowledge Distillation for Quantized Deep Neural Networks
AAAI 2021 FracBits: Mixed Precision Quantization via Fractional Bit-Widths [code]
AAAI 2021 Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision
AAAI 2021 Training Binary Neural Network without Batch Normalization for Image Super-Resolution
AAAI 2021 SA-BNN: State-Aware Binary Neural Network
CVPR 2021 Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks. [code]
CVPR 2021 Diversifying Sample Generation for Accurate Data-Free Quantization
CVPR 2021 Learnable Companding Quantization for Accurate Low-bit Neural Networks
CVPR 2021 Zero-shot Adversarial Quantization
CVPR 2021 Network Quantization with Element-wise Gradient Scaling [code]
CVPR 2021 Automated Log-Scale Quantization for Low-Cost Deep Neural Networks
CVPR 2021 QPP: Real-Time Quantization Parameter Prediction for Deep Neural Networks
ICLR 2021 Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming [code]
ICLR 2021 BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction [code]
ICLR 2021 Neural gradients are near-lognormal: improved quantized and sparse training
ICLR 2021 Training with Quantization Noise for Extreme Model Compression
ICLR 2021 Incremental few-shot learning via vector quantization in deep embedded space
ICLR 2021 Degree-Quant: Quantization-Aware Training for Graph Neural Networks [code]
ICLR 2021 BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization
ICLR 2021 Simple Augmentation Goes a Long Way: ADRL for DNN Quantization
ICML 2021 Differentiable dynamic quantization with mixed precision and adaptive resolution
ICML 2021 HAWQV3: Dyadic Neural Network Quantization [code]
ICML 2021 Accurate Post Training Quantization With Small Calibration Sets
ICML 2021 I-BERT: Integer-only BERT Quantization [code]
NeurIPS 2021 Post-Training Quantization for Vision Transformer
NeurIPS 2021 Post-Training Sparsity-Aware Quantization [code]
NeurIPS 2021 BatchQuant: Quantized-for-all Architecture Search with Robust Quantizer
NeurIPS 2021 Qimera: Data-free quantization with synthetic boundary supporting samples [code]

2020

AAAI 2020 Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT [code]
AAAI 2020 Towards Accurate Low Bit-Width Quantization with Multiple Phase Adaptations
CVPR 2020 ZeroQ: A Novel Zero Shot Quantization Framework [code]
CVPR 2020 LSQ+: Improving Low-bit Quantization Through Learnable Offsets and Better Initialization
CVPR 2020 AdaBits: Neural Network Quantization With Adaptive Bit-Widths [code]
CVPR 2020 Adaptive Loss-aware Quantization for Multi-bit Networks [code]
ECCV 2020 HMQ: Hardware Friendly Mixed Precision Quantization Block for CNNs [code]
ECCV 2020 Generative Low-bitwidth Data Free Quantization [code]
ICML 2020 Towards Accurate Post-training Quantization for Reparameterized Models [code]
ICML 2020 Up or Down? Adaptive Rounding for Post-Training Quantization [code]
NeurIPS 2020 Searching for Low-Bit Weights in Quantized Neural Networks [code]
NeurIPS 2020 Robust Quantization: One Model to Rule Them All [code]