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 1201–1225 of 4925 papers

TitleStatusHype
Quantization Design for Deep Learning-Based CSI Feedback—0
VocalEyes: Enhancing Environmental Perception for the Visually Impaired through Vision-Language Models and Distance-Aware Object Detection—0
Lightweight Multimodal Artificial Intelligence Framework for Maritime Multi-Scene Recognition—0
Task Vector Quantization for Memory-Efficient Model MergingCode0
Non-vacuous Generalization Bounds for Deep Neural Networks without any modification to the trained models—0
Synchronized Video-to-Audio Generation via Mel Quantization-Continuum Decomposition—0
Breaking the Limits of Quantization-Aware Defenses: QADT-R for Robustness Against Patch-Based Adversarial Attacks in QNNs—0
Post-Training Quantization for Diffusion Transformer via Hierarchical Timestep Grouping—0
Seeing Delta Parameters as JPEG Images: Data-Free Delta Compression with Discrete Cosine Transform—0
SAQ-SAM: Semantically-Aligned Quantization for Segment Anything Model—0
TR-DQ: Time-Rotation Diffusion Quantization—0
Towards Superior Quantization Accuracy: A Layer-sensitive Approach—0
PathVQ: Reforming Computational Pathology Foundation Model for Whole Slide Image Analysis via Vector Quantization—0
Does Acceleration Cause Hidden Instability in Vision Language Models? Uncovering Instance-Level Divergence Through a Large-Scale Empirical Study—0
CASP: Compression of Large Multimodal Models Based on Attention SparsityCode0
Discrete Contrastive Learning for Diffusion Policies in Autonomous Driving—0
Frequency Autoregressive Image Generation with Continuous Tokens—0
VQEL: Enabling Self-Developed Symbolic Language in Agents through Vector Quantization in Emergent Language Games—0
End-to-End Human Pose Reconstruction from Wearable Sensors for 6G Extended Reality SystemsCode0
Universality of Layer-Level Entropy-Weighted Quantization Beyond Model Architecture and Size—0
LVLM-Compress-Bench: Benchmarking the Broader Impact of Large Vision-Language Model CompressionCode0
AHCPTQ: Accurate and Hardware-Compatible Post-Training Quantization for Segment Anything Model—0
On the Relation Between Speech Quality and Quantized Latent Representations of Neural Codecs—0
Fast Jet Tagging with MLP-Mixers on FPGAs—0
English K_Quantization of LLMs Does Not Disproportionately Diminish Multilingual Performance—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