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 4501–4550 of 4925 papers

TitleStatusHype
Experimental results on palmvein-based personal recognition by multi-snapshot fusion of textural features—0
Explicit Loss-Error-Aware Quantization for Low-Bit Deep Neural Networks—0
Exploiting Change Blindness for Video Coding: Perspectives from a Less Promising User Study—0
Exploiting Intelligent Reflecting Surfaces in NOMA Networks: Joint Beamforming Optimization—0
Exploiting Latent Properties to Optimize Neural Codecs—0
Exploiting Modern Hardware for High-Dimensional Nearest Neighbor Search—0
Exploiting Non-uniform Quantization for Enhanced ILC in Wideband Digital Pre-distortion—0
Exploiting Offset-guided Network for Pose Estimation and Tracking—0
Exploiting Weight Redundancy in CNNs: Beyond Pruning and Quantization—0
Exploration of Activation Fault Reliability in Quantized Systolic Array-Based DNN Accelerators—0
Explore Cross-Codec Quality-Rate Convex Hulls Relation for Adaptive Streaming—0
Explore the Potential of CNN Low Bit Training—0
Exploring Automatic Gym Workouts Recognition Locally On Wearable Resource-Constrained Devices—0
Exploring Extreme Quantization in Spiking Language Models—0
Exploring FPGA designs for MX and beyond—0
Exploring Model Invariance with Discrete Search for Ultra-Low-Bit Quantization—0
Exploring Neural Networks Quantization via Layer-Wise Quantization Analysis—0
Exploring Semantic Segmentation on the DCT Representation—0
Exposing Hardware Building Blocks to Machine Learning Frameworks—0
Bracket Diffusion: HDR Image Generation by Consistent LDR Denoising—0
Extreme Compression for Pre-trained Transformers Made Simple and Efficient—0
Extreme Image Compression using Fine-tuned VQGANs—0
Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM—0
Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation—0
Face recognition using color local binary pattern from mutually independent color channels—0
Factorized Visual Tokenization and Generation—0
FactorizeNet: Progressive Depth Factorization for Efficient Network Architecture Exploration Under Quantization Constraints—0
False Detection (Positives and Negatives) in Object Detection—0
FAMES: Fast Approximate Multiplier Substitution for Mixed-Precision Quantized DNNs--Down to 2 Bits!—0
FantastIC4: A Hardware-Software Co-Design Approach for Efficiently Running 4bit-Compact Multilayer Perceptrons—0
FAQ: Mitigating the Impact of Faults in the Weight Memory of DNN Accelerators through Fault-Aware Quantization—0
FAQS: Communication-efficient Federate DNN Architecture and Quantization Co-Search for personalized Hardware-aware Preferences—0
Fast Autoregressive Models for Continuous Latent Generation—0
Fast binary embeddings, and quantized compressed sensing with structured matrices—0
Fast, Compact, and High Quality LSTM-RNN Based Statistical Parametric Speech Synthesizers for Mobile Devices—0
Fast DistilBERT on CPUs—0
FAST: DNN Training Under Variable Precision Block Floating Point with Stochastic Rounding—0
Fastening the Initial Access in 5G NR Sidelink for 6G V2X Networks—0
Faster Inference of Integer SWIN Transformer by Removing the GELU Activation—0
Faster Neural Net Inference via Forests of Sparse Oblique Decision Trees—0
FastICARL: Fast Incremental Classifier and Representation Learning with Efficient Budget Allocation in Audio Sensing Applications—0
Fast Implementation of 4-bit Convolutional Neural Networks for Mobile Devices—0
Fast Inference of Tree Ensembles on ARM Devices—0
Fast Jet Tagging with MLP-Mixers on FPGAs—0
Fast Large-Scale Discrete Optimization Based on Principal Coordinate Descent—0
Fast learning rates with heavy-tailed losses—0
Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification—0
FastMamba: A High-Speed and Efficient Mamba Accelerator on FPGA with Accurate Quantization—0
Fast on-line signature recognition based on VQ with time modeling—0
Fast Orthogonal Projection Based on Kronecker Product—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