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 3651–3700 of 4925 papers

TitleStatusHype
OL-DN: Online learning based dual-domain network for HEVC intra frame quality enhancement—0
On Accelerating Edge AI: Optimizing Resource-Constrained Environments—0
On Adaptive Transmission for Distributed Detection in Energy Harvesting Wireless Sensor Networks with Limited Fusion Center Feedback—0
On a Relation Between the Rate-Distortion Function and Optimal Transport—0
On Calibration of Modern Quantized Efficient Neural Networks—0
Once Quantized for All: Progressively Searching for Quantized Compact Models—0
On-demand Quantization for Green Federated Generative Diffusion in Mobile Edge Networks—0
On Designing Modulation for Over-the-Air Computation -- Part I: Noise-Aware Design—0
On-device AI: Quantization-aware Training of Transformers in Time-Series—0
On-Device Learning with Binary Neural Networks—0
On-Device Qwen2.5: Efficient LLM Inference with Model Compression and Hardware Acceleration—0
On Distributed Quantization for Classification—0
One-Bit-Aided Modulo Sampling for DOA Estimation—0
One-Bit Channel Estimation for IRS-aided Millimeter-Wave Massive MU-MISO System—0
One-Bit Direct Position Determination of Narrowband Gaussian Signals—0
One-bit LFMCW Radar: Spectrum Analysis and Target Detection—0
One-Bit MIMO Detection: From Global Maximum-Likelihood Detector to Amplitude Retrieval Approach—0
One-Bit OFDM Receivers via Deep Learning—0
One-Bit Quantization and Sparsification for Multiclass Linear Classification with Strong Regularization—0
One-Bit Sigma-Delta DFRC Waveform Design: Using Quantization Noise for Radar Probing—0
One-Bit Sigma-Delta modulation on the circle—0
One-Bit Target Detection in Collocated MIMO Radar and Performance Degradation Analysis—0
On Effects of Compression with Hyperdimensional Computing in Distributed Randomized Neural Networks—0
On Efficient Constructions of Checkpoints—0
One-Index Vector Quantization Based Adversarial Attack on Image Classification—0
One Model for All Quantization: A Quantized Network Supporting Hot-Swap Bit-Width Adjustment—0
One-pass Multiple Conformer and Foundation Speech Systems Compression and Quantization Using An All-in-one Neural Model—0
One QuantLLM for ALL: Fine-tuning Quantized LLMs Once for Efficient Deployments—0
One-Shot Model for Mixed-Precision Quantization—0
One Weight Bitwidth to Rule Them All—0
On Hardening DNNs against Noisy Computations—0
On Image Registration and Subpixel Estimation—0
On Large-Scale Retrieval: Binary or n-ary Coding?—0
On Leaky-Integrate-and Fire as Spike-Train-Quantization Operator on Dirac-Superimposed Continuous-Time Signals—0
Online Categorical Subspace Learning for Sketching Big Data with Misses—0
Online Embedding Compression for Text Classification using Low Rank Matrix Factorization—0
Online Learned Continual Compression with Stacked Quantization Modules—0
Online Meta Adaptation for Variable-Rate Learned Image Compression—0
Online Model Compression for Federated Learning with Large Models—0
Online Product Quantization—0
Online Signature Recognition: A Biologically Inspired Feature Vector Splitting Approach—0
On Minimizing Symbol Error Rate Over Fading Channels with Low-Resolution Quantization—0
On Neural Architecture Search for Resource-Constrained Hardware Platforms—0
On Noncommutative Quantum Mechanics and the Black-Scholes Model—0
On One-Bit Quantization—0
On the Arrow of Inference—0
On Periodic Functions as Regularizers for Quantization of Neural Networks—0
On Quantizing Implicit Neural Representations—0
On Randomized Distributed Coordinate Descent with Quantized Updates—0
On Recursive State Estimation for Linear State-Space Models Having Quantized Output Data—0
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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