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

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Showing 4651–4700 of 4925 papers

TitleStatusHype
From Text to Source: Results in Detecting Large Language Model-Generated Content—0
Fronthaul Compression and Passive Beamforming Design for Intelligent Reflecting Surface-aided Cloud Radio Access Networks—0
Fronthaul-Constrained Distributed Radar Sensing—0
Fronthaul Quantization-Aware MU-MIMO Precoding for Sum Rate Maximization—0
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary—0
FSpiNN: An Optimization Framework for Memory- and Energy-Efficient Spiking Neural Networks—0
FTL: A universal framework for training low-bit DNNs via Feature Transfer—0
Full-Duplex Beyond Self-Interference: The Unlimited Sensing Way—0
Full-Duplex Cell-Free mMIMO Systems: Analysis and Decentralized Optimization—0
Full-Duplex Massive MIMO Cellular Networks with Low Resolution ADC/DAC—0
FullPack: Full Vector Utilization for Sub-Byte Quantized Inference on General Purpose CPUs—0
Full-Precision Free Binary Graph Neural Networks—0
Full-Resolution Encoder-Decoder Networks with Multi-Scale Feature Fusion for Human Pose Estimation—0
Fully Digital Second-order Level-crossing Sampling ADC for Data Saving in Sensing Sparse Signals—0
Fully Distributed and Quantized Algorithm for MPC-based Autonomous Vehicle Platooning Optimization—0
Homomorphic Encryption-Enabled Distance-Based Distributed Formation Control with Distance Mismatch Estimators—0
Fully Quantized Network for Object Detection—0
Fully Quantized Transformer for Machine Translation—0
Functional Invariants to Watermark Large Transformers—0
Functional quantization of rough volatility and applications to volatility derivatives—0
Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach—0
Fundamental Trade-offs in Quantized Hybrid Radar Fusion: A CRB-Rate Perspective—0
FunQuant: A R package to perform quantization in the context of rare events and time-consuming simulations—0
FusionSAM: Latent Space driven Segment Anything Model for Multimodal Fusion and Segmentation—0
Fuzzy-Based Dialectical Non-Supervised Image Classification and Clustering—0
Fuzzy Norm-Explicit Product Quantization for Recommender Systems—0
FxP-QNet: A Post-Training Quantizer for the Design of Mixed Low-Precision DNNs with Dynamic Fixed-Point Representation—0
GA-GAN: CT reconstruction from Biplanar DRRs using GAN with Guided Attention—0
GALA: Geometry-Aware Local Adaptive Grids for Detailed 3D Generation—0
Galaxy classification: A machine learning analysis of GAMA catalogue data—0
GANCompress: GAN-Enhanced Neural Image Compression with Binary Spherical Quantization—0
GAQAT: gradient-adaptive quantization-aware training for domain generalization—0
Gaussian Approximation of Quantization Error for Estimation from Compressed Data—0
Gaussian AutoEncoder—0
Gaussian Mixture Vector Quantization with Aggregated Categorical Posterior—0
Gaussian Rate-Distortion-Perception Coding and Entropy-Constrained Scalar Quantization—0
GDRQ: Group-based Distribution Reshaping for Quantization—0
GEB-1.3B: Open Lightweight Large Language Model—0
GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning—0
Gender Bias Amplification During Speed-Quality Optimization in Neural Machine Translation—0
Generalization Error Analysis of Quantized Compressive Learning—0
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles—0
Line Spectrum Estimation and Detection with Few-bit ADCs: Theoretical Analysis and Generalized NOMP Algorithm—0
Generalized residual vector quantization for large scale data—0
General Point Model with Autoencoding and Autoregressive—0
General Purpose Text Embeddings from Pre-trained Language Models for Scalable Inference—0
Generating 3D Brain Tumor Regions in MRI using Vector-Quantization Generative Adversarial Networks—0
Generating diverse and natural text-to-speech samples using a quantized fine-grained VAE and auto-regressive prosody prior—0
Generative AI in Cybersecurity: A Comprehensive Review of LLM Applications and Vulnerabilities—0
Generative Design of Hardware-aware DNNs—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