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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2001–2050 of 4925 papers

TitleStatusHype
Gradient _1 Regularization for Quantization Robustness—0
Gradient-Free Neural Network Training on the Edge—0
Does Video Compression Impact Tracking Accuracy?—0
GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training—0
BiQGEMM: Matrix Multiplication with Lookup Table For Binary-Coding-based Quantized DNNs—0
Granger Causality from Quantized Measurements—0
Countering Adversarial Examples: Combining Input Transformation and Noisy Training—0
GranQ: Granular Zero-Shot Quantization with Channel-Wise Activation Scaling in QAT—0
Graph-Based Depth Denoising & Dequantization for Point Cloud Enhancement—0
Graph-Collaborated Auto-Encoder Hashing for Multi-view Binary Clustering—0
An Empirical Study of Low Precision Quantization for TinyML—0
Does compressing activations help model parallel training?—0
Greedy Selection for Heterogeneous Sensors—0
Greener yet Powerful: Taming Large Code Generation Models with Quantization—0
An Embedded Iris Recognition System Optimization using Dynamically ReconfigurableDecoder with LDPC Codes—0
Do All MobileNets Quantize Poorly? Gaining Insights into the Effect of Quantization on Depthwise Separable Convolutional Networks Through the Eyes of Multi-scale Distributional Dynamics—0
DNQ: Dynamic Network Quantization—0
DNN Quantization with Attention—0
Gridless Multisnapshot Variational Line Spectral Estimation from Coarsely Quantized Samples—0
Group channel pruning and spatial attention distilling for object detection—0
Grouped Sequency-arranged Rotation: Optimizing Rotation Transformation for Quantization for Free—0
Group Invariant Deep Representations for Image Instance Retrieval—0
SwiftPrune: Hessian-Free Weight Pruning for Large Language Models—0
Hybrid and Non-Uniform DNN quantization methods using Retro Synthesis data for efficient inference—0
Group Sparse Coding—0
CQ-VAE: Coordinate Quantized VAE for Uncertainty Estimation with Application to Disk Shape Analysis from Lumbar Spine MRI Images—0
DNN Memory Footprint Reduction via Post-Training Intra-Layer Multi-Precision Quantization—0
GSVR: 2D Gaussian-based Video Representation for 800+ FPS with Hybrid Deformation Field—0
Guaranteed Quantization Error Computation for Neural Network Model Compression—0
CRB Analysis for Mixed-ADC Based DOA Estimation—0
Biologically Plausible Learning on Neuromorphic Hardware Architectures—0
Bioinspired Cortex-based Fast Codebook Generation—0
Gull: A Generative Multifunctional Audio Codec—0
GWQ: Gradient-Aware Weight Quantization for Large Language Models—0
Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks—0
DNA-TEQ: An Adaptive Exponential Quantization of Tensors for DNN Inference—0
HACK: Homomorphic Acceleration via Compression of the Key-Value Cache for Disaggregated LLM Inference—0
An Efficient Network with Novel Quantization Designed for Massive MIMO CSI Feedback—0
Hadamard Domain Training with Integers for Class Incremental Quantized Learning—0
HadaNets: Flexible Quantization Strategies for Neural Networks—0
HadaNorm: Diffusion Transformer Quantization through Mean-Centered Transformations—0
HALL-E: Hierarchical Neural Codec Language Model for Minute-Long Zero-Shot Text-to-Speech Synthesis—0
Human Activity Recognition on Microcontrollers with Quantized and Adaptive Deep Neural Networks—0
Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks—0
HALO: Hardware-aware quantization with low critical-path-delay weights for LLM acceleration—0
LANA: Latency Aware Network Acceleration—0
BinaryViT: Towards Efficient and Accurate Binary Vision Transformers—0
An Efficient Index for Visual Search in Appearance-based SLAM—0
Diversifying Sample Generation for Accurate Data-Free Quantization—0
QVGen: Pushing the Limit of Quantized Video Generative Models—0
Show:102550
← PrevPage 41 of 99Next →
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