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 1851–1900 of 4925 papers

TitleStatusHype
Deep Hashing via Householder QuantizationCode0
Generative Diffusion Models for Lattice Field Theory—0
Learned layered coding for Successive Refinement in the Wyner-Ziv Problem—0
Attention or Convolution: Transformer Encoders in Audio Language Models for Inference Efficiency—0
AFPQ: Asymmetric Floating Point Quantization for LLMsCode1
Effective Quantization for Diffusion Models on CPUs—0
Divergent Token Metrics: Measuring degradation to prune away LLM components -- and optimize quantization—0
AWEQ: Post-Training Quantization with Activation-Weight Equalization for Large Language Models—0
The bottleneck and ceiling effects in quantized tracking control of heterogeneous multi-agent systems under DoS attacks—0
Crop Disease Classification using Support Vector Machines with Green Chromatic Coordinate (GCC) and Attention based feature extraction for IoT based Smart Agricultural Applications—0
Efficient LLM Inference on CPUsCode2
Q-Learning for Stochastic Control under General Information Structures and Non-Markovian Environments—0
Resource Constrained Semantic Segmentation for Waste SortingCode0
Exploring Post-Training Quantization of Protein Language ModelsCode0
A Principled Hierarchical Deep Learning Approach to Joint Image Compression and Classification—0
Conditional Denoising Diffusion Probabilistic Models for Data Reconstruction Enhancement in Wireless Communications—0
QWID: Quantized Weed Identification Deep neural networkCode0
Atom: Low-bit Quantization for Efficient and Accurate LLM ServingCode2
Embedding in Recommender Systems: A SurveyCode1
High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise—0
Med-DANet V2: A Flexible Dynamic Architecture for Efficient Medical Volumetric Segmentation—0
NIF: A Fast Implicit Image Compression with Bottleneck Layers and Modulated Sinusoidal ActivationsCode0
Edge AI-Based Vein Detector for Efficient Venipuncture in the Antecubital FossaCode1
Distributed Delay-Tolerant Strategies for Equality-Constraint Sum-Preserving Resource Allocation—0
ZeroQuant-HERO: Hardware-Enhanced Robust Optimized Post-Training Quantization Framework for W8A8 Transformers—0
Codebook Features: Sparse and Discrete Interpretability for Neural NetworksCode1
Deep Imbalanced Regression via Hierarchical Classification Adjustment—0
Transmitting Data Through Reconfigurable Intelligent Surface: A Spatial Sigma-Delta Modulation Approach—0
Wide Flat Minimum Watermarking for Robust Ownership Verification of GANs—0
Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte CarloCode0
General Point Model with Autoencoding and Autoregressive—0
Structured Multi-Track Accompaniment Arrangement via Style Prior ModellingCode1
LLM-FP4: 4-Bit Floating-Point Quantized TransformersCode2
Random Entity Quantization for Parameter-Efficient Compositional Knowledge Graph RepresentationCode0
LDPC Decoding with Degree-Specific Neural Message Weights and RCQ Decoding—0
Federated learning compression designed for lightweight communicationsCode0
VQ-NeRF: Vector Quantization Enhances Implicit Neural Representations—0
Deep Autoencoder-based Z-Interference Channels with Perfect and Imperfect CSI—0
Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly DetectionCode1
Spatial Sigma-Delta Modulation for Coarsely Quantized Massive MIMO Downlink: Flexible Designs by Convex Optimization—0
An Overview on IEEE 802.11bf: WLAN Sensing—0
Zero-Shot Sharpness-Aware Quantization for Pre-trained Language Models—0
VQ-NeRF: Neural Reflectance Decomposition and Editing with Vector Quantization—0
Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning—0
A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challenge—0
Matrix Compression via Randomized Low Rank and Low Precision FactorizationCode1
Watermarking LLMs with Weight QuantizationCode1
Functional Invariants to Watermark Large Transformers—0
BitNet: Scaling 1-bit Transformers for Large Language ModelsCode2
TEQ: Trainable Equivalent Transformation for Quantization of LLMs—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