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 1601–1650 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
Convolutional Neural Networks Quantization with Attention—0
Convolutional Neural Network Quantization using Generalized Gamma Distribution—0
Asymmetric Learned Image Compression with Multi-Scale Residual Block, Importance Map, and Post-Quantization Filtering—0
Convolutional neural network compression for natural language processing—0
Asymmetric Deep Semantic Quantization for Image Retrieval—0
Convex Quantization Preserves Logconcavity—0
Asymmetric Correlation Quantization Hashing for Cross-modal Retrieval—0
Aggregated Learning: A Deep Learning Framework Based on Information-Bottleneck Vector Quantization—0
Convergence Theory of Generalized Distributed Subgradient Method with Random Quantization—0
AsymKV: Enabling 1-Bit Quantization of KV Cache with Layer-Wise Asymmetric Quantization Configurations—0
Convergence Rates for Regularized Optimal Transport via Quantization—0
Convergence rate of Tsallis entropic regularized optimal transport—0
A Generalized Zero-Shot Quantization of Deep Convolutional Neural Networks via Learned Weights Statistics—0
Convergence rate of sign stochastic gradient descent for non-convex functions—0
Convergence of Federated Learning over a Noisy Downlink—0
A Survey on Transformer Compression—0
Contrastive Quant: Quantization Makes Stronger Contrastive Learning—0
CoST: Contrastive Quantization based Semantic Tokenization for Generative Recommendation—0
A Survey on Model Compression for Large Language Models—0
A General Family of Stochastic Proximal Gradient Methods for Deep Learning—0
Accurate INT8 Training Through Dynamic Block-Level Fallback—0
Contrastive Mutual Information Maximization for Binary Neural Networks—0
A Survey on Methods and Theories of Quantized Neural Networks—0
Continuous Speech Synthesis using per-token Latent Diffusion—0
A Survey on Learning to Hash—0
Show:102550
← PrevPage 33 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