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 1601–1625 of 4925 papers

TitleStatusHype
Countering Adversarial Examples: Combining Input Transformation and Noisy Training—0
Asynchronous Federated Learning with Bidirectional Quantized Communications and Buffered Aggregation—0
Asymptotic Unbiased Sample Sampling to Speed Up Sharpness-Aware Minimization—0
Cost-Driven Hardware-Software Co-Optimization of Machine Learning Pipelines—0
Cost-Aware Routing for Efficient Text-To-Image Generation—0
Asymptotic tracking control of dynamic reference over homomorphically encrypted data with finite modulus—0
AgileIR: Memory-Efficient Group Shifted Windows Attention for Agile Image Restoration—0
A Channelized Binning Method for Extraction of Dominant Color Pixel Value—0
CosSGD: Communication-Efficient Federated Learning with a Simple Cosine-Based Quantization—0
Correlation Hashing Network for Efficient Cross-Modal Retrieval—0
Asymptotic stabilization under homomorphic encryption: A re-encryption free method—0
Correlated Quantization for Faster Nonconvex Distributed Optimization—0
Correlated quantization for distributed mean estimation and optimization—0
Asymptotic Performance Analysis of Large-Scale Active IRS-Aided Wireless Network—0
Aggressive Post-Training Compression on Extremely Large Language Models—0
Coreset-Based Neural Network Compression—0
Asymptotic Analysis of One-bit Quantized Box-Constrained Precoding in Large-Scale Multi-User Systems—0
CorBin-FL: A Differentially Private Federated Learning Mechanism using Common Randomness—0
Coordinated Per-Antenna Power Minimization for Multicell Massive MIMO Systems with Low-Resolution Data Converters—0
Asymptotically Optimal Closed-Form Phase Configuration of 1-bit RISs via Sign Alignment—0
Aggregating empirical evidence from data strategy studies: a case on model quantization—0
Accurate Sine-Wave Amplitude Measurements Using Nonlinearly Quantized Data—0
4-bit Quantization of LSTM-based Speech Recognition Models—0
Inference Optimizations for Large Language Models: Effects, Challenges, and Practical Considerations—0
Asymmetric Learning Vector Quantization for Efficient Nearest Neighbor Classification in Dynamic Time Warping Spaces—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