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 1351–1400 of 4925 papers

TitleStatusHype
A Novel Physics-based Channel Model for Reconfigurable Intelligent Surface-assisted Multi-user Communication Systems—0
Adaptive Joint Optimization for 3D Reconstruction with Differentiable Rendering—0
End-to-end fully-binarized network design: from Generic Learned Thermometer to Block Pruning—0
Cancer Subtyping via Embedded Unsupervised Learning on Transcriptomics Data—0
CAMBI: Contrast-aware Multiscale Banding Index—0
A Novel Light Field Coding Scheme Based on Deep Belief Network & Weighted Binary Images for Additive Layered Displays—0
CALM: Co-evolution of Algorithms and Language Model for Automatic Heuristic Design—0
A Novel Hybrid Precoder With Low-Resolution Phase Shifters and Fronthaul Capacity Limitation—0
Adaptive Integrate-and-Fire Time Encoding Machine with Quantization—0
Cactus Mechanisms: Optimal Differential Privacy Mechanisms in the Large-Composition Regime—0
A Novel Framework for Image-to-image Translation and Image Compression—0
CacheQuant: Comprehensively Accelerated Diffusion Models—0
A Novel Chaotic Uniform Quantizer for Speech Coding—0
Accelerated Distance Computation with Encoding Tree for High Dimensional Data—0
End-to-end Keyword Spotting using Neural Architecture Search and Quantization—0
End-to-End Optimized Speech Coding with Deep Neural Networks—0
A Novel Audio Representation for Music Genre Identification in MIR—0
CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge—0
Byzantine-Resilient Secure Federated Learning—0
A Novel Approach to Quantized Matrix Completion Using Huber Loss Measure—0
Adaptive Dither Voting for Robust Spatial Verification—0
Bullion: A Column Store for Machine Learning—0
Building an Efficiency Pipeline: Commutativity and Cumulativeness of Efficiency Operators for Transformers—0
A notion of stability for k-means clustering—0
BTEL: A Binary Tree Encoding Approach for Visual Localization—0
Another Way to the Top: Exploit Contextual Clustering in Learned Image Coding—0
Adaptive Dithering Using Curved Markov-Gaussian Noise in the Quantized Domain for Mapping SDR to HDR Image—0
Accelerated AI Inference via Dynamic Execution Methods—0
BRICS: Bi-level feature Representation of Image CollectionS—0
An Optimization Framework for Federated Edge Learning—0
BRIEDGE: EEG-Adaptive Edge AI for Multi-Brain to Multi-Robot Interaction—0
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization—0
A Carbon Tracking Model for Federated Learning: Impact of Quantization and Sparsification—0
Bridging the Modality Gap: Softly Discretizing Audio Representation for LLM-based Automatic Speech Recognition—0
Bridging the Gap between Gaussian Diffusion Models and Universal Quantization for Image Compression—0
An NMF Perspective on Binary Hashing—0
Bridging the Gap between Continuous and Informative Discrete Representations by Random Product Quantization—0
Bridging the Accuracy Gap for 2-bit Quantized Neural Networks (QNN)—0
AnnArbor: Approximate Nearest Neighbors Using Arborescence Coding—0
Implementing Keyword Spotting on the MCUX947 Microcontroller with Integrated NPU—0
Encoder-Quantization-Motion-based Video Quality Metrics—0
Bridging Continuous and Discrete Tokens for Autoregressive Visual Generation—0
Anisotropic oracle inequalities in noisy quantization—0
Breaking the waves: asymmetric random periodic features for low-bitrate kernel machines—0
Breaking the Limits of Quantization-Aware Defenses: QADT-R for Robustness Against Patch-Based Adversarial Attacks in QNNs—0
An Investigation on Different Underlying Quantization Schemes for Pre-trained Language Models—0
Adaptive Dataset Quantization—0
Breaking the Bias: Recalibrating the Attention of Industrial Anomaly Detection—0
Breaking Determinism: Fuzzy Modeling of Sequential Recommendation Using Discrete State Space Diffusion Model—0
An Inquiry into Datacenter TCO for LLM Inference with FP8—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