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

Showing 17511800 of 4925 papers

TitleStatusHype
Cross-Layer Optimization for Fault-Tolerant Deep Learning0
TinySAM: Pushing the Envelope for Efficient Segment Anything ModelCode2
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data HeterogeneityCode0
Towards Efficient Verification of Quantized Neural NetworksCode0
Mini-GPTs: Efficient Large Language Models through Contextual PruningCode1
Find the Lady: Permutation and Re-Synchronization of Deep Neural NetworksCode0
Compact 3D Scene Representation via Self-Organizing Gaussian GridsCode3
SimQ-NAS: Simultaneous Quantization Policy and Neural Architecture Search0
Quantized Decoder in Learned Image Compression for Deterministic Reconstruction0
Power-Efficient Sampling0
Post-Training Quantization for Re-parameterization via Coarse & Fine Weight SplittingCode0
StyleSinger: Style Transfer for Out-of-Domain Singing Voice SynthesisCode2
SPT: Fine-Tuning Transformer-based Language Models Efficiently with SparsificationCode0
Adaptive Computation Modules: Granular Conditional Computation For Efficient InferenceCode0
IQNet: Image Quality Assessment Guided Just Noticeable Difference Prefiltering For Versatile Video Coding0
ZeroQuant(4+2): Redefining LLMs Quantization with a New FP6-Centric Strategy for Diverse Generative TasksCode2
Design Space Exploration of Low-Bit Quantized Neural Networks for Visual Place Recognition0
USM-Lite: Quantization and Sparsity Aware Fine-tuning for Speech Recognition with Universal Speech Models0
CBQ: Cross-Block Quantization for Large Language Models0
When Bio-Inspired Computing meets Deep Learning: Low-Latency, Accurate, & Energy-Efficient Spiking Neural Networks from Artificial Neural Networks0
IDKM: Memory Efficient Neural Network Quantization via Implicit, Differentiable k-Means0
Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization0
Decoupling Meta-Reinforcement Learning with Gaussian Task Contexts and SkillsCode0
Neural Architecture Codesign for Fast Bragg Peak Analysis0
FP8-BERT: Post-Training Quantization for Transformer0
QMGeo: Differentially Private Federated Learning via Stochastic Quantization with Mixed Truncated Geometric Distribution0
Automotive Radar Sensing with Sparse Linear Arrays Using One-Bit Hankel Matrix Completion0
Understanding the Effect of Model Compression on Social Bias in Large Language ModelsCode0
Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the EdgeCode0
Efficient Quantization Strategies for Latent Diffusion Models0
An Experimental Study: Assessing the Combined Framework of WavLM and BEST-RQ for Text-to-Speech Synthesis0
GenQ: Quantization in Low Data Regimes with Generative Synthetic DataCode0
Rate-splitting Multiple Access for Hierarchical HAP-LAP Networks under Limited Fronthaul0
SmoothQuant+: Accurate and Efficient 4-bit Post-Training WeightQuantization for LLMCode1
Does Vector Quantization Fail in Spatio-Temporal Forecasting? Exploring a Differentiable Sparse Soft-Vector Quantization ApproachCode1
Enhancing Kinship Verification through Multiscale Retinex and Combined Deep-Shallow features0
All Rivers Run to the Sea: Private Learning with Asymmetric Flows0
Unified learning-based lossy and lossless JPEG recompression0
PLUM: Improving Inference Efficiency By Leveraging Repetition-Sparsity Trade-OffCode0
QuantAttack: Exploiting Dynamic Quantization to Attack Vision TransformersCode0
Low-Precision Mixed-Computation Models for Inference on Edge0
Adaptive Resource Allocation for Semantic Communication Networks0
Physics Inspired Criterion for Pruning-Quantization Joint LearningCode0
The Cost of Compression: Investigating the Impact of Compression on Parametric Knowledge in Language ModelsCode0
Improving the Robustness of Quantized Deep Neural Networks to White-Box Attacks using Stochastic Quantization and Information-Theoretic Ensemble Training0
Routing-Guided Learned Product Quantization for Graph-Based Approximate Nearest Neighbor SearchCode0
A New Old Idea: Beam-Steering Reflectarrays for Efficient Sub-THz Multiuser MIMO0
CompGS: Smaller and Faster Gaussian Splatting with Vector QuantizationCode2
Language Embedded 3D Gaussians for Open-Vocabulary Scene UnderstandingCode1
Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices0
Show:102550
← PrevPage 36 of 99Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FQ-ViT (ViT-L)Top-1 Accuracy (%)85.03Unverified
2FQ-ViT (ViT-B)Top-1 Accuracy (%)83.31Unverified
3FQ-ViT (Swin-B)Top-1 Accuracy (%)82.97Unverified
4FQ-ViT (Swin-S)Top-1 Accuracy (%)82.71Unverified
5FQ-ViT (DeiT-B)Top-1 Accuracy (%)81.2Unverified
6FQ-ViT (Swin-T)Top-1 Accuracy (%)80.51Unverified
7FQ-ViT (DeiT-S)Top-1 Accuracy (%)79.17Unverified
8Xception W8A8Top-1 Accuracy (%)78.97Unverified
9ADLIK-MO-ResNet50-W4A4Top-1 Accuracy (%)77.88Unverified
10ADLIK-MO-ResNet50-W3A4Top-1 Accuracy (%)77.34Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_3MAP160,327.04Unverified
2DTQMAP0.79Unverified
#ModelMetricClaimedVerifiedStatus
1OutEffHop-Bert_basePerplexity6.3Unverified
2OutEffHop-Bert_basePerplexity6.21Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy98.13Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy92.92Unverified
#ModelMetricClaimedVerifiedStatus
1SSD ResNet50 V1 FPN 640x640MAP34.3Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-495.13Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-496.38Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_5All84,809,664Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy99.8Unverified