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 901–925 of 4925 papers

TitleStatusHype
PrivQuant: Communication-Efficient Private Inference with Quantized Network/Protocol Co-Optimization—0
SLiM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight CompressionCode1
QEFT: Quantization for Efficient Fine-Tuning of LLMsCode0
DeltaDQ: Ultra-High Delta Compression for Fine-Tuned LLMs via Group-wise Dropout and Separate Quantization—0
ZipVL: Efficient Large Vision-Language Models with Dynamic Token Sparsification—0
ACCEPT: Adaptive Codebook for Composite and Efficient Prompt TuningCode0
M^2-ViT: Accelerating Hybrid Vision Transformers with Two-Level Mixed Quantization—0
DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation—0
CrossQuant: A Post-Training Quantization Method with Smaller Quantization Kernel for Precise Large Language Model Compression—0
MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete DiffusionCode0
Scalable Representation Learning for Multimodal Tabular Transactions—0
Q-VLM: Post-training Quantization for Large Vision-Language ModelsCode2
Hallo2: Long-Duration and High-Resolution Audio-Driven Portrait Image AnimationCode7
QuAILoRA: Quantization-Aware Initialization for LoRA—0
Scaling Laws for Mixed quantization in Large Language Models—0
JPEG Inspired Deep LearningCode0
Perceptual Quality Assessment of Trisoup-Lifting Encoded 3D Point CloudsCode0
Gesture2Text: A Generalizable Decoder for Word-Gesture Keyboards in XR Through Trajectory Coarse Discretization and Pre-training—0
Variable Bitrate Residual Vector Quantization for Audio Coding—0
QERA: an Analytical Framework for Quantization Error Reconstruction—0
Accelerating Error Correction Code TransformersCode0
Restructuring Vector Quantization with the Rotation TrickCode4
Covering Numbers for Deep ReLU Networks with Applications to Function Approximation and Nonparametric Regression—0
QT-DoG: Quantization-aware Training for Domain GeneralizationCode1
MC-MoE: Mixture Compressor for Mixture-of-Experts LLMs Gains MoreCode2
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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