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 2051–2100 of 4925 papers

TitleStatusHype
EdgeFusion: On-Device Text-to-Image Generation—0
LongVQ: Long Sequence Modeling with Vector Quantization on Structured Memory—0
QGen: On the Ability to Generalize in Quantization Aware Training—0
Neural Network Approach for Non-Markovian Dissipative Dynamics of Many-Body Open Quantum Systems—0
Variational quantization for state space modelsCode0
Comprehensive Survey of Model Compression and Speed up for Vision Transformers—0
Quantization of Large Language Models with an Overdetermined Basis—0
Efficient and accurate neural field reconstruction using resistive memory—0
TMPQ-DM: Joint Timestep Reduction and Quantization Precision Selection for Efficient Diffusion Models—0
SNN4Agents: A Framework for Developing Energy-Efficient Embodied Spiking Neural Networks for Autonomous AgentsCode0
Bullion: A Column Store for Machine Learning—0
Full-Duplex Beyond Self-Interference: The Unlimited Sensing Way—0
Lossy Image Compression with Foundation Diffusion Models—0
1-bit Quantized On-chip Hybrid Diffraction Neural Network Enabled by Authentic All-optical Fully-connected Architecture—0
Frame Quantization of Neural Networks—0
Edge-Efficient Deep Learning Models for Automatic Modulation Classification: A Performance Analysis—0
CQIL: Inference Latency Optimization with Concurrent Computation of Quasi-Independent LayersCode0
Differentiable Search for Finding Optimal Quantization Strategy—0
Collaborative Edge AI Inference over Cloud-RAN—0
Encoder-Quantization-Motion-based Video Quality Metrics—0
Physics of Language Models: Part 3.3, Knowledge Capacity Scaling Laws—0
Investigating the Impact of Quantization on Adversarial Robustness—0
Exploring Quantization and Mapping Synergy in Hardware-Aware Deep Neural Network AcceleratorsCode0
David and Goliath: An Empirical Evaluation of Attacks and Defenses for QNNs at the Deep EdgeCode0
Gull: A Generative Multifunctional Audio Codec—0
Weakly Supervised Deep Hyperspherical Quantization for Image RetrievalCode0
Nanometer Scanning with Micrometer Sensing: Beating Quantization Constraints in Lissajous Trajectory Tracking—0
What Happens When Small Is Made Smaller? Exploring the Impact of Compression on Small Data Pretrained Language Models—0
Fine-Tuning, Quantization, and LLMs: Navigating Unintended Outcomes—0
TinyVQA: Compact Multimodal Deep Neural Network for Visual Question Answering on Resource-Constrained Devices—0
Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation RegularizationCode0
DI-Retinex: Digital-Imaging Retinex Theory for Low-Light Image Enhancement—0
CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech—0
Cherry on Top: Parameter Heterogeneity and Quantization in Large Language Models—0
DNN Memory Footprint Reduction via Post-Training Intra-Layer Multi-Precision Quantization—0
NeRFCodec: Neural Feature Compression Meets Neural Radiance Fields for Memory-Efficient Scene Representation—0
Minimize Quantization Output Error with Bias CompensationCode0
On the Effect of Quantization on Dynamic Mode Decomposition—0
RefQSR: Reference-based Quantization for Image Super-Resolution Networks—0
A Novel Audio Representation for Music Genre Identification in MIR—0
Instance-Aware Group Quantization for Vision Transformers—0
Towards Variable and Coordinated Holistic Co-Speech Motion Generation—0
Accurate Block Quantization in LLMs with Outliers—0
Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs—0
QNCD: Quantization Noise Correction for Diffusion ModelsCode0
Meta-Heuristic Fronthaul Bit Allocation for Cell-free Massive MIMO Systems—0
Uncertainty-Aware Deep Video Compression with Ensembles—0
Within the Dynamic Context: Inertia-aware 3D Human Modeling with Pose Sequence—0
Oh! We Freeze: Improving Quantized Knowledge Distillation via Signal Propagation Analysis for Large Language Models—0
Order of Compression: A Systematic and Optimal Sequence to Combinationally Compress CNN—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