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 1701–1750 of 4925 papers

TitleStatusHype
Thinking in Granularity: Dynamic Quantization for Image Super-Resolution by Intriguing Multi-Granularity CluesCode0
CorBin-FL: A Differentially Private Federated Learning Mechanism using Common Randomness—0
Reduced bit median quantization: A middle process for Efficient Image Compression—0
PTQ4ADM: Post-Training Quantization for Efficient Text Conditional Audio Diffusion Models—0
TalkMosaic: Interactive PhotoMosaic with Multi-modal LLM Q&A Interactions—0
Impact of ML Optimization Tactics on Greener Pre-Trained ML Models—0
NDVQ: Robust Neural Audio Codec with Normal Distribution-Based Vector Quantization—0
Scaling FP8 training to trillion-token LLMs—0
Art and Science of Quantizing Large-Scale Models: A Comprehensive Overview—0
Pareto Data Framework: Steps Towards Resource-Efficient Decision Making Using Minimum Viable Data (MVD)—0
Low Frame-rate Speech Codec: a Codec Designed for Fast High-quality Speech LLM Training and Inference—0
Exploring the Trade-Offs: Quantization Methods, Task Difficulty, and Model Size in Large Language Models From Edge to GiantCode0
LASERS: LAtent Space Encoding for Representations with Sparsity for Generative Modeling—0
Forearm Ultrasound based Gesture Recognition on Edge—0
Improving Statistical Significance in Human Evaluation of Automatic Metrics via Soft Pairwise Accuracy—0
Language Models and Retrieval Augmented Generation for Automated Structured Data Extraction from Diagnostic Reports—0
MesonGS: Post-training Compression of 3D Gaussians via Efficient Attribute Transformation—0
Robust Training of Neural Networks at Arbitrary Precision and Sparsity—0
Privacy-Preserving SAM Quantization for Efficient Edge Intelligence in Healthcare—0
Investigating Disentanglement in a Phoneme-level Speech Codec for Prosody Modeling—0
Efficient and Reliable Vector Similarity Search Using Asymmetric Encoding with NAND-Flash for Many-Class Few-Shot Learning—0
Dequantization of a signal from two parallel quantized observations—0
Adaptive Error-Bounded Hierarchical Matrices for Efficient Neural Network Compression—0
Distributed Convolutional Neural Network Training on Mobile and Edge Clusters—0
NVRC: Neural Video Representation Compression—0
STORE: Streamlining Semantic Tokenization and Generative Recommendation with A Single LLM—0
AgileIR: Memory-Efficient Group Shifted Windows Attention for Agile Image Restoration—0
Rate-Constrained Quantization for Communication-Efficient Federated Learning—0
Estimating the Completeness of Discrete Speech Units—0
ECG Biometric Authentication Using Self-Supervised Learning for IoT Edge Sensors—0
TriplePlay: Enhancing Federated Learning with CLIP for Non-IID Data and Resource Efficiency—0
Distributed Optimization with Finite Bit Adaptive Quantization for Efficient Communication and Precision Enhancement—0
SGC-VQGAN: Towards Complex Scene Representation via Semantic Guided Clustering Codebook—0
Blind-Adaptive Quantizers—0
OPAL: Outlier-Preserved Microscaling Quantization Accelerator for Generative Large Language Models—0
Investigating Privacy Bias in Training Data of Language Models—0
WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking—0
LAST: Language Model Aware Speech Tokenization—0
Recursive Quantization for L_2 Stabilization of a Finite Capacity Stochastic Control Loop with Intermittent State Observations—0
CoAst: Validation-Free Contribution Assessment for Federated Learning based on Cross-Round Valuation—0
Gaussian Rate-Distortion-Perception Coding and Entropy-Constrained Scalar Quantization—0
Task-Oriented Communication for Graph Data: A Graph Information Bottleneck Approach—0
Learning Task-Based Trainable Neuromorphic ADCs via Power-Aware Distillation—0
Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model—0
Foundations of Large Language Model Compression -- Part 1: Weight QuantizationCode0
Optimization and Deployment of Deep Neural Networks for PPG-based Blood Pressure Estimation Targeting Low-power Wearables—0
Robust Clustering on High-Dimensional Data with Stochastic QuantizationCode0
Compressing VAE-Based Out-of-Distribution Detectors for Embedded Deployment—0
One-Index Vector Quantization Based Adversarial Attack on Image Classification—0
Edge AI: Evaluation of Model Compression Techniques for Convolutional Neural Networks—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