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 1951–1975 of 4925 papers

TitleStatusHype
Bit Efficient Quantization for Deep Neural Networks—0
Generative AI in Cybersecurity: A Comprehensive Review of LLM Applications and Vulnerabilities—0
A blob method for inhomogeneous diffusion with applications to multi-agent control and sampling—0
Generative Design of Hardware-aware DNNs—0
Generative Diffusion Models for Lattice Field Theory—0
HEQuant: Marrying Homomorphic Encryption and Quantization for Communication-Efficient Private Inference—0
Generative QoE Modeling: A Lightweight Approach for Telecom Networks—0
Generative Semantic Communication for Text-to-Speech Synthesis—0
Hexcute: A Tile-based Programming Language with Automatic Layout and Task-Mapping Synthesis—0
DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models—0
Convergence Rates for Regularized Optimal Transport via Quantization—0
A Biresolution Spectral Framework for Product Quantization—0
Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript—0
Geometry and clustering with metrics derived from separable Bregman divergences—0
Gesture2Text: A Generalizable Decoder for Word-Gesture Keyboards in XR Through Trajectory Coarse Discretization and Pre-training—0
Getting Free Bits Back from Rotational Symmetries in LLMs—0
BiTAT: Neural Network Binarization with Task-dependent Aggregated Transformation—0
An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms—0
HDR Imaging With One-Bit Quantization—0
GIF2Video: Color Dequantization and Temporal Interpolation of GIF images—0
Don't Fear the Bit Flips: Optimized Coding Strategies for Binary Classification—0
Givens Coordinate Descent Methods for Rotation Matrix Learning in Trainable Embedding Indexes—0
Domain Generalization on Efficient Acoustic Scene Classification using Residual Normalization—0
BiSup: Bidirectional Quantization Error Suppression for Large Language Models—0
AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training—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