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 1451–1500 of 4925 papers

TitleStatusHype
HEAM: High-Efficiency Approximate Multiplier Optimization for Deep Neural NetworksCode0
Autoregressive Co-Training for Learning Discrete Speech RepresentationsCode0
GANQ: GPU-Adaptive Non-Uniform Quantization for Large Language ModelsCode0
Deep Learning as a Mixed Convex-Combinatorial Optimization ProblemCode0
FTT-NAS: Discovering Fault-Tolerant Convolutional Neural ArchitectureCode0
Deep Image Compression via End-to-End LearningCode0
FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-designCode0
Post-training Model Quantization Using GANs for Synthetic Data GenerationCode0
Post-Training Quantization for Re-parameterization via Coarse & Fine Weight SplittingCode0
A2Q: Accumulator-Aware Quantization with Guaranteed Overflow AvoidanceCode0
Efficient Federated Intrusion Detection in 5G ecosystem using optimized BERT-based modelCode0
FP4DiT: Towards Effective Floating Point Quantization for Diffusion TransformersCode0
Deep Hashing via Householder QuantizationCode0
FLoCoRA: Federated learning compression with low-rank adaptationCode0
Floating-Point Quantization Analysis of Multi-Layer Perceptron Artificial Neural NetworksCode0
Flexible Mixed Precision Quantization for Learned Image CompressionCode0
FlexRound: Learnable Rounding based on Element-wise Division for Post-Training QuantizationCode0
FlashEval: Towards Fast and Accurate Evaluation of Text-to-image Diffusion Generative ModelsCode0
Deep Convolutional AutoEncoder-based Lossy Image CompressionCode0
FINN-L: Library Extensions and Design Trade-off Analysis for Variable Precision LSTM Networks on FPGAsCode0
Flexible framework for audio reconstructionCode0
Foundations of Large Language Model Compression -- Part 1: Weight QuantizationCode0
Deep Compressive Autoencoder for Action Potential Compression in Large-Scale Neural RecordingCode0
Efficient Large-scale Approximate Nearest Neighbor Search on the GPUCode0
AlignedKV: Reducing Memory Access of KV-Cache with Precision-Aligned QuantizationCode0
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman CodingCode0
DeepCABAC: A Universal Compression Algorithm for Deep Neural NetworksCode0
Finding Non-Uniform Quantization Schemes using Multi-Task Gaussian ProcessesCode0
Find the Lady: Permutation and Re-Synchronization of Deep Neural NetworksCode0
Deep attention-based classification network for robust depth predictionCode0
Efficient Mixed Precision Quantization in Graph Neural NetworksCode0
Generalized Learning Vector Quantization for Classification in Randomized Neural Networks and Hyperdimensional ComputingCode0
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data HeterogeneityCode0
Federated learning compression designed for lightweight communicationsCode0
Decoupling Meta-Reinforcement Learning with Gaussian Task Contexts and SkillsCode0
Federated Learning via Plurality VoteCode0
FEDZIP: A Compression Framework for Communication-Efficient Federated LearningCode0
Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN InferenceCode0
Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial ExamplesCode0
Federated Classification in Hyperbolic Spaces via Secure Aggregation of Convex HullsCode0
Fast Supervised Discrete Hashing and its AnalysisCode0
AMED: Automatic Mixed-Precision Quantization for Edge DevicesCode0
Automated Cancer Subtyping via Vector Quantization Mutual Information MaximizationCode0
Fast Private Kernel Density Estimation via Locality Sensitive QuantizationCode0
Algorithm and VLSI Design for 1-bit Data Detection in Massive MIMO-OFDMCode0
FDDH: Fast Discriminative Discrete Hashing for Large-Scale Cross-Modal RetrievalCode0
David and Goliath: An Empirical Evaluation of Attacks and Defenses for QNNs at the Deep EdgeCode0
Data Upcycling Knowledge Distillation for Image Super-ResolutionCode0
Faster Binary Embeddings for Preserving Euclidean DistancesCode0
Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary SeminormsCode0
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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