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 976–1000 of 4925 papers

TitleStatusHype
INT-FlashAttention: Enabling Flash Attention for INT8 QuantizationCode2
VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language ModelsCode4
BitQ: Tailoring Block Floating Point Precision for Improved DNN Efficiency on Resource-Constrained DevicesCode1
PTQ4RIS: Post-Training Quantization for Referring Image SegmentationCode0
LLaMa-SciQ: An Educational Chatbot for Answering Science MCQ—0
Communication and Energy Efficient Federated Learning using Zero-Order Optimization Technique—0
A Formalization of Image Vectorization by Region Merging—0
Twin Network Augmentation: A Novel Training Strategy for Improved Spiking Neural Networks and Efficient Weight Quantization—0
TCSinger: Zero-Shot Singing Voice Synthesis with Style Transfer and Multi-Level Style ControlCode3
Ultra-low latency quantum-inspired machine learning predictors implemented on FPGA—0
Disentanglement with Factor Quantized Variational AutoencodersCode0
MICSim: A Modular Simulator for Mixed-signal Compute-in-Memory based AI AcceleratorCode1
SPAQ-DL-SLAM: Towards Optimizing Deep Learning-based SLAM for Resource-Constrained Embedded Platforms—0
Thinking in Granularity: Dynamic Quantization for Image Super-Resolution by Intriguing Multi-Granularity CluesCode0
DilateQuant: Accurate and Efficient Diffusion Quantization via Weight Dilation—0
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
NDVQ: Robust Neural Audio Codec with Normal Distribution-Based Vector Quantization—0
Scaling FP8 training to trillion-token LLMs—0
Impact of ML Optimization Tactics on Greener Pre-Trained ML Models—0
Art and Science of Quantizing Large-Scale Models: A Comprehensive Overview—0
Low Frame-rate Speech Codec: a Codec Designed for Fast High-quality Speech LLM Training and Inference—0
Pareto Data Framework: Steps Towards Resource-Efficient Decision Making Using Minimum Viable Data (MVD)—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