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 401–425 of 4925 papers

TitleStatusHype
Fractional Skipping: Towards Finer-Grained Dynamic CNN InferenceCode1
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN TrainingCode1
EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion ModelsCode1
End-to-End Rate-Distortion Optimized Learned Hierarchical Bi-Directional Video CompressionCode1
Enabling Binary Neural Network Training on the EdgeCode1
GAN Slimming: All-in-One GAN Compression by A Unified Optimization FrameworkCode1
Generalizable Mixed-Precision Quantization via Attribution Rank PreservationCode1
Generalized Product Quantization Network for Semi-supervised Image RetrievalCode1
APQ: Joint Search for Network Architecture, Pruning and Quantization PolicyCode1
Generative Adversarial Super-Resolution at the Edge with Knowledge DistillationCode1
EMQ: Evolving Training-free Proxies for Automated Mixed Precision QuantizationCode1
End-to-End Rate-Distortion Optimized 3D Gaussian RepresentationCode1
Enhancing Generalization of Universal Adversarial Perturbation through Gradient AggregationCode1
Anonymizing Speech: Evaluating and Designing Speaker Anonymization TechniquesCode1
Embedding in Recommender Systems: A SurveyCode1
Adaptive Debanding FilterCode1
Efficient-VDVAE: Less is moreCode1
Environmental Sound Classification on the Edge: A Pipeline for Deep Acoustic Networks on Extremely Resource-Constrained DevicesCode1
EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion ModelsCode1
HALO: Hadamard-Assisted Lower-Precision Optimization for LLMsCode1
Hard Sample Matters a Lot in Zero-Shot QuantizationCode1
Adaptive Data-Free QuantizationCode1
Efficient and Robust Quantization-aware Training via Adaptive Coreset SelectionCode1
HHF: Hashing-guided Hinge Function for Deep Hashing RetrievalCode1
EFaR 2023: Efficient Face Recognition CompetitionCode1
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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