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

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Showing 1051–1100 of 4925 papers

TitleStatusHype
Column-wise Quantization of Weights and Partial Sums for Accurate and Efficient Compute-In-Memory AcceleratorsCode0
Low-Precision Stochastic Gradient Langevin DynamicsCode0
Low-Precision Random Fourier Features for Memory-Constrained Kernel ApproximationCode0
Low dimensional representation of multi-patient flow cytometry datasets using optimal transport for minimal residual disease detection in leukemiaCode0
APSQ: Additive Partial Sum Quantization with Algorithm-Hardware Co-DesignCode0
A Programmable Approach to Neural Network CompressionCode0
Low-complexity acoustic scene classification for multi-device audio: analysis of DCASE 2021 Challenge systemsCode0
Low Precision Decentralized Distributed Training over IID and non-IID DataCode0
LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural NetworksCode0
Multi-Class Uncertainty Calibration via Mutual Information Maximization-based BinningCode0
Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector QuantizationCode0
Loss-aware Weight Quantization of Deep NetworksCode0
Loss Landscape Analysis for Reliable Quantized ML Models for Scientific SensingCode0
Log-Time K-Means Clustering for 1D Data: Novel Approaches with Proof and ImplementationCode0
HQOD: Harmonious Quantization for Object DetectionCode0
Loss Aware Post-training QuantizationCode0
LoTA-QAF: Lossless Ternary Adaptation for Quantization-Aware Fine-TuningCode0
Accelerating Generalized Linear Models with MLWeaving: A One-Size-Fits-All System for Any-precision Learning (Technical Report)Code0
Low-bit Model Quantization for Deep Neural Networks: A SurveyCode0
Lipschitz Continuity Retained Binary Neural NetworkCode0
Approximate spectral clustering using both reference vectors and topology of the network generated by growing neural gasCode0
LISA: Learning Interpretable Skill Abstractions from LanguageCode0
Approximate spectral clustering density-based similarity for noisy datasetsCode0
LiteLMGuard: Seamless and Lightweight On-Device Prompt Filtering for Safeguarding Small Language Models against Quantization-induced Risks and VulnerabilitiesCode0
Linearly Converging Error Compensated SGDCode0
Lightweight Deep Learning Based Channel Estimation for Extremely Large-Scale Massive MIMO SystemsCode0
Accelerating Error Correction Code TransformersCode0
LiFT: Lightweight, FPGA-tailored 3D object detection based on LiDAR dataCode0
Approximate Message Passing with Parameter Estimation for Heavily Quantized MeasurementsCode0
LFZip: Lossy compression of multivariate floating-point time series data via improved predictionCode0
Light Multi-segment Activation for Model CompressionCode0
Leveraging Continuously Differentiable Activation Functions for Learning in Quantized Noisy EnvironmentsCode0
LegalEval-Q: A New Benchmark for The Quality Evaluation of LLM-Generated Legal TextCode0
Lightweight Client-Side Chinese/Japanese Morphological Analyzer Based on Online LearningCode0
LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and QuantizationCode0
Low-bit Quantization for Deep Graph Neural Networks with Smoothness-aware Message PropagationCode0
Neural Network Compression of ACAS Xu Early Prototype is Unsafe: Closed-Loop Verification through Quantized State BackreachabilityCode0
Applying generative neural networks for fast simulations of the ALICE (CERN) experimentCode0
Learning Space Partitions for Nearest Neighbor SearchCode0
Communication-Efficient Federated Learning via Clipped Uniform QuantizationCode0
Dequantization and Color Transfer with Diffusion ModelsCode0
Climate Finance BenchCode0
Learning Semantic Textual Similarity via Topic-informed Discrete Latent VariablesCode0
Automatic Neural Network Compression by Sparsity-Quantization Joint Learning: A Constrained Optimization-based ApproachCode0
Learning Physical-Layer Communication with Quantized FeedbackCode0
CLAQ: Pushing the Limits of Low-Bit Post-Training Quantization for LLMsCode0
Learning Convolutional Transforms for Lossy Point Cloud Geometry CompressionCode0
Learning Frequency-Specific Quantization Scaling in VVC for Standard-Compliant Task-driven Image CodingCode0
Learning compact binary descriptors with unsupervised deep neural networksCode0
Learning Bag-of-Features Pooling for Deep Convolutional Neural NetworksCode0
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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