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 601–625 of 4925 papers

TitleStatusHype
Confounding Tradeoffs for Neural Network QuantizationCode1
Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval PerformanceCode1
A Memory Efficient Baseline for Open Domain Question AnsweringCode1
BAND-2k: Banding Artifact Noticeable Database for Banding Detection and Quality AssessmentCode1
Compression with Bayesian Implicit Neural RepresentationsCode1
CPLLM: Clinical Prediction with Large Language ModelsCode1
Designing Large Foundation Models for Efficient Training and Inference: A SurveyCode1
Joint Privacy Enhancement and Quantization in Federated LearningCode1
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network QuantizationCode1
D^2-DPM: Dual Denoising for Quantized Diffusion Probabilistic ModelsCode1
SimCC: a Simple Coordinate Classification Perspective for Human Pose EstimationCode1
Benchmarking Quantized Neural Networks on FPGAs with FINNCode1
BAGUA: Scaling up Distributed Learning with System RelaxationsCode1
Data-Free Quantization Through Weight Equalization and Bias CorrectionCode1
Analog Foundation ModelsCode1
Accurate KV Cache Quantization with Outlier Tokens TracingCode1
Compress Any Segment Anything Model (SAM)Code1
DeCoAR 2.0: Deep Contextualized Acoustic Representations with Vector QuantizationCode1
Beyond Learned Metadata-based Raw Image ReconstructionCode1
Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMsCode1
Learning Statistical Texture for Semantic SegmentationCode1
Beyond Preserved Accuracy: Evaluating Loyalty and Robustness of BERT CompressionCode1
It's All In the Teacher: Zero-Shot Quantization Brought Closer to the TeacherCode1
Deep Geometry Post-Processing for Decompressed Point CloudsCode1
Comprehensive Graph-conditional Similarity Preserving Network for Unsupervised Cross-modal HashingCode1
Show:102550
← PrevPage 25 of 197Next →
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