SOTAVerified

Quantization

Quantization is a promising technique to reduce the computation cost of neural network training, which can replace high-cost floating-point numbers (e.g., float32) with low-cost fixed-point numbers (e.g., int8/int16).

Source: Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers

Papers

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Showing 651–700 of 4925 papers

TitleStatusHype
ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank ResidualsCode1
A Survey on Inference Optimization Techniques for Mixture of Experts ModelsCode3
Autoregressive Video Generation without Vector QuantizationCode4
Self-control: A Better Conditional Mechanism for Masked Autoregressive Model—0
On the Compression of Language Models for Code: An Empirical Study on CodeBERT—0
More Tokens, Lower Precision: Towards the Optimal Token-Precision Trade-off in KV Cache Compression—0
VidTok: A Versatile and Open-Source Video TokenizerCode3
Apollo-Forecast: Overcoming Aliasing and Inference Speed Challenges in Language Models for Time Series Forecasting—0
Fast and Slow Gradient Approximation for Binary Neural Network OptimizationCode0
Quantifying Climate Change Impacts on Renewable Energy Generation: A Super-Resolution Recurrent Diffusion Model—0
QPruner: Probabilistic Decision Quantization for Structured Pruning in Large Language Models—0
FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation—0
CSR:Achieving 1 Bit Key-Value Cache via Sparse Representation—0
Relation-Guided Adversarial Learning for Data-free Knowledge TransferCode1
MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion ModelsCode1
VRVVC: Variable-Rate NeRF-Based Volumetric Video Compression—0
Nanoscaling Floating-Point (NxFP): NanoMantissa, Adaptive Microexponents, and Code Recycling for Direct-Cast Compression of Large Language Models—0
ProFe: Communication-Efficient Decentralized Federated Learning via Distillation and Prototypes—0
TrimLLM: Progressive Layer Dropping for Domain-Specific LLMs—0
Efficient Quantization-Aware Training on Segment Anything Model in Medical Images and Its DeploymentCode0
Enhancing Off-Grid One-Bit DOA Estimation with Learning-Based Sparse Bayesian Approach for Non-Uniform Sparse Array—0
Adaptive Quantization Resolution and Power Control for Federated Learning over Cell-free Networks—0
TinySubNets: An efficient and low capacity continual learning strategyCode0
Memory-Efficient 4-bit Preconditioned Stochastic Optimization—0
Progressive Compression with Universally Quantized Diffusion Models—0
Efficient Generative Modeling with Residual Vector Quantization-Based Tokens—0
VQTalker: Towards Multilingual Talking Avatars through Facial Motion Tokenization—0
TTAQ: Towards Stable Post-training Quantization in Continuous Domain Adaptation—0
MVQ:Towards Efficient DNN Compression and Acceleration with Masked Vector Quantization—0
SCBench: A KV Cache-Centric Analysis of Long-Context MethodsCode5
Panacea: Novel DNN Accelerator using Accuracy-Preserving Asymmetric Quantization and Energy-Saving Bit-Slice Sparsity—0
CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language ModelsCode11
DQA: An Efficient Method for Deep Quantization of Deep Neural Network Activations—0
Lexico: Extreme KV Cache Compression via Sparse Coding over Universal DictionariesCode1
CRVQ: Channel-relaxed Vector Quantization for Extreme Compression of LLMs—0
Optimising TinyML with Quantization and Distillation of Transformer and Mamba Models for Indoor Localisation on Edge Devices—0
On Round-Off Errors and Gaussian Blur in Superresolution and in Image Registration—0
Breaking the Bias: Recalibrating the Attention of Industrial Anomaly Detection—0
TurboAttention: Efficient Attention Approximation For High Throughputs LLMs—0
Low-Rank Correction for Quantized LLMs—0
Machine learning-driven conservative-to-primitive conversion in hybrid piecewise polytropic and tabulated equations of state—0
Post-Training Non-Uniform Quantization for Convolutional Neural Networks—0
QuantFormer: Learning to Quantize for Neural Activity Forecasting in Mouse Visual Cortex—0
FP=xINT:A Low-Bit Series Expansion Algorithm for Post-Training Quantization—0
Compression for Better: A General and Stable Lossless Compression Framework—0
Federated Split Learning with Model Pruning and Gradient Quantization in Wireless Networks—0
Efficiency Meets Fidelity: A Novel Quantization Framework for Stable Diffusion—0
Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization—0
Fuzzy Norm-Explicit Product Quantization for Recommender Systems—0
SizeGS: Size-aware Compression of 3D Gaussians with Hierarchical Mixed Precision Quantization—0
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All datasetsImageNetCIFAR-10Wiki-40BAgeDB-30CFP-FPCOCO (Common Objects in Context)IJB-BIJB-CKnowledge-based:LFW

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FQ-ViT (ViT-L)Top-1 Accuracy (%)85.03—Unverified
2FQ-ViT (ViT-B)Top-1 Accuracy (%)83.31—Unverified
3FQ-ViT (Swin-B)Top-1 Accuracy (%)82.97—Unverified
4FQ-ViT (Swin-S)Top-1 Accuracy (%)82.71—Unverified
5FQ-ViT (DeiT-B)Top-1 Accuracy (%)81.2—Unverified
6FQ-ViT (Swin-T)Top-1 Accuracy (%)80.51—Unverified
7FQ-ViT (DeiT-S)Top-1 Accuracy (%)79.17—Unverified
8Xception W8A8Top-1 Accuracy (%)78.97—Unverified
9ADLIK-MO-ResNet50-W4A4Top-1 Accuracy (%)77.88—Unverified
10ADLIK-MO-ResNet50-W3A4Top-1 Accuracy (%)77.34—Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_3MAP160,327.04—Unverified
2DTQMAP0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1OutEffHop-Bert_basePerplexity6.3—Unverified
2OutEffHop-Bert_basePerplexity6.21—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy98.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy92.92—Unverified
#ModelMetricClaimedVerifiedStatus
1SSD ResNet50 V1 FPN 640x640MAP34.3—Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-495.13—Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-496.38—Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_5All84,809,664—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy99.8—Unverified