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

Showing 651700 of 4925 papers

TitleStatusHype
Anchor-based Plain Net for Mobile Image Super-ResolutionCode1
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed TrainingCode1
BinaryDM: Accurate Weight Binarization for Efficient Diffusion ModelsCode1
Binary Latent DiffusionCode1
Catastrophic Failure of LLM Unlearning via QuantizationCode1
NeuraLUT: Hiding Neural Network Density in Boolean Synthesizable FunctionsCode1
ConveRT: Efficient and Accurate Conversational Representations from TransformersCode1
Convolutional Autoencoder-Based Phase Shift Feedback Compression for Intelligent Reflecting Surface-Assisted Wireless SystemsCode1
Binary TTC: A Temporal Geofence for Autonomous NavigationCode1
Injecting Domain Adaptation with Learning-to-hash for Effective and Efficient Zero-shot Dense RetrievalCode1
LiMuSE: Lightweight Multi-modal Speaker ExtractionCode1
NIPQ: Noise proxy-based Integrated Pseudo-QuantizationCode1
Lightweight Diffusion Models for Resource-Constrained Semantic CommunicationCode1
Continuous Visual Autoregressive Generation via Score MaximizationCode1
Hybrid Inverted Index Is a Robust Accelerator for Dense RetrievalCode1
DQS3D: Densely-matched Quantization-aware Semi-supervised 3D DetectionCode1
Lightweight Super-Resolution Head for Human Pose EstimationCode1
Linear-Time Self Attention with Codeword Histogram for Efficient RecommendationCode1
DVD-Quant: Data-free Video Diffusion Transformers QuantizationCode1
L-GreCo: Layerwise-Adaptive Gradient Compression for Efficient and Accurate Deep LearningCode1
Lexico: Extreme KV Cache Compression via Sparse Coding over Universal DictionariesCode1
Continual Learning via Bit-Level Information PreservingCode1
Context-aware Communication for Multi-agent Reinforcement LearningCode1
EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion ModelsCode1
Learning to Groove with Inverse Sequence TransformationsCode1
AdANNS: A Framework for Adaptive Semantic SearchCode1
Learning to Improve Image Compression without Changing the Standard DecoderCode1
Conditional Coding and Variable Bitrate for Practical Learned Video CodingCode1
EA-3DGS: Efficient and Adaptive 3D Gaussians with Highly Enhanced Quality for outdoor scenesCode1
Effectiveness of self-supervised pre-training for speech recognitionCode1
Confounding Tradeoffs for Neural Network QuantizationCode1
BitStack: Any-Size Compression of Large Language Models in Variable Memory EnvironmentsCode1
Learning to Structure an Image with Few ColorsCode1
COMQ: A Backpropagation-Free Algorithm for Post-Training QuantizationCode1
Bitwidth-Adaptive Quantization-Aware Neural Network Training: A Meta-Learning ApproachCode1
Online Learned Continual Compression with Adaptive Quantization ModulesCode1
Designing Large Foundation Models for Efficient Training and Inference: A SurveyCode1
Benchmarking of DL Libraries and Models on Mobile DevicesCode1
Optimal Discrete Beamforming of RIS-Aided Wireless Communications: An Inner Product Maximization ApproachCode1
BL-JUNIPER: A CNN-Assisted Framework for Perceptual Video Coding Leveraging Block-Level JNDCode1
CondiQuant: Condition Number Based Low-Bit Quantization for Image Super-ResolutionCode1
Optimizing Binary and Ternary Neural Network Inference on RRAM Crossbars using CIM-ExplorerCode1
Learning Statistical Texture for Semantic SegmentationCode1
Least squares binary quantization of neural networksCode1
Lite Transformer with Long-Short Range AttentionCode1
Learning a Single Model with a Wide Range of Quality Factors for JPEG Image Artifacts RemovalCode1
A Little Bit More: Bitplane-Wise Bit-Depth RecoveryCode1
Efficient and Robust Quantization-aware Training via Adaptive Coreset SelectionCode1
Learning Cross-Scale Weighted Prediction for Efficient Neural Video CompressionCode1
Compressing LLMs: The Truth is Rarely Pure and Never SimpleCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FQ-ViT (ViT-L)Top-1 Accuracy (%)85.03Unverified
2FQ-ViT (ViT-B)Top-1 Accuracy (%)83.31Unverified
3FQ-ViT (Swin-B)Top-1 Accuracy (%)82.97Unverified
4FQ-ViT (Swin-S)Top-1 Accuracy (%)82.71Unverified
5FQ-ViT (DeiT-B)Top-1 Accuracy (%)81.2Unverified
6FQ-ViT (Swin-T)Top-1 Accuracy (%)80.51Unverified
7FQ-ViT (DeiT-S)Top-1 Accuracy (%)79.17Unverified
8Xception W8A8Top-1 Accuracy (%)78.97Unverified
9ADLIK-MO-ResNet50-W4A4Top-1 Accuracy (%)77.88Unverified
10ADLIK-MO-ResNet50-W3A4Top-1 Accuracy (%)77.34Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_3MAP160,327.04Unverified
2DTQMAP0.79Unverified
#ModelMetricClaimedVerifiedStatus
1OutEffHop-Bert_basePerplexity6.3Unverified
2OutEffHop-Bert_basePerplexity6.21Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy98.13Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy92.92Unverified
#ModelMetricClaimedVerifiedStatus
1SSD ResNet50 V1 FPN 640x640MAP34.3Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-495.13Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-496.38Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_5All84,809,664Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy99.8Unverified