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 1–25 of 4925 papers

TitleStatusHype
Efficient Deployment of Spiking Neural Networks on SpiNNaker2 for DVS Gesture Recognition Using Neuromorphic Intermediate RepresentationCode0
An End-to-End DNN Inference Framework for the SpiNNaker2 Neuromorphic MPSoC—0
Angle Estimation of a Single Source with Massive Uniform Circular Arrays—0
Task-Specific Audio Coding for Machines: Machine-Learned Latent Features Are Codes for That Machine—0
Quantized Rank Reduction: A Communications-Efficient Federated Learning Scheme for Network-Critical Applications—0
MGVQ: Could VQ-VAE Beat VAE? A Generalizable Tokenizer with Multi-group QuantizationCode2
Lightweight Federated Learning over Wireless Edge Networks—0
Vision Foundation Models as Effective Visual Tokenizers for Autoregressive Image Generation—0
Compress Any Segment Anything Model (SAM)Code1
MGVQ: Could VQ-VAE Beat VAE? A Generalizable Tokenizer with Multi-group QuantizationCode2
OpenDPDv2: A Unified Learning and Optimization Framework for Neural Network Digital PredistortionCode0
Semantic Certainty Assessment in Vector Retrieval Systems: A Novel Framework for Embedding Quality Evaluation—0
EdgeCodec: Onboard Lightweight High Fidelity Neural Compressor with Residual Vector QuantizationCode0
QS4D: Quantization-aware training for efficient hardware deployment of structured state-space sequential models—0
GSVR: 2D Gaussian-based Video Representation for 800+ FPS with Hybrid Deformation Field—0
any4: Learned 4-bit Numeric Representation for LLMsCode2
Rethinking Discrete Tokens: Treating Them as Conditions for Continuous Autoregressive Image Synthesis—0
CycleVAR: Repurposing Autoregressive Model for Unsupervised One-Step Image TranslationCode1
Analysis of Null Related Beampattern Measures and Signal Quantization Effects for Linear Differential Microphone Arrays—0
PsyLite Technical ReportCode0
Joint Quantization and Pruning Neural Networks Approach: A Case Study on FSO Receivers—0
OLALa: Online Learned Adaptive Lattice Codes for Heterogeneous Federated LearningCode0
Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language ModelsCode1
DipSVD: Dual-importance Protected SVD for Efficient LLM Compression—0
Cross-Layer Discrete Concept Discovery for Interpreting Language Models—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