SOTAVerified

Knowledge Distillation

Knowledge distillation is the process of transferring knowledge from a large model to a smaller one. While large models (such as very deep neural networks or ensembles of many models) have higher knowledge capacity than small models, this capacity might not be fully utilized.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1201–1225 of 4240 papers

TitleStatusHype
LookALike: Human Mimicry based collaborative decision making—0
Group-Mix SAM: Lightweight Solution for Industrial Assembly Line Applications—0
Histo-Genomic Knowledge Distillation For Cancer Prognosis From Histopathology Whole Slide ImagesCode1
Recurrent Drafter for Fast Speculative Decoding in Large Language ModelsCode3
Adapting OC20-trained EquiformerV2 Models for High-Entropy Materials—0
Select and Distill: Selective Dual-Teacher Knowledge Transfer for Continual Learning on Vision-Language Models—0
Open-Vocabulary Object Detection with Meta Prompt Representation and Instance Contrastive Optimization—0
Knowledge Distillation in YOLOX-ViT for Side-Scan Sonar Object DetectionCode2
SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike StreamsCode1
MT-PATCHER: Selective and Extendable Knowledge Distillation from Large Language Models for Machine TranslationCode0
Distilling Named Entity Recognition Models for Endangered Species from Large Language Models—0
Training Self-localization Models for Unseen Unfamiliar Places via Teacher-to-Student Data-Free Knowledge Transfer—0
An Efficient End-to-End Approach to Noise Invariant Speech Features via Multi-Task LearningCode0
CoroNetGAN: Controlled Pruning of GANs via Hypernetworks—0
LIX: Implicitly Infusing Spatial Geometric Prior Knowledge into Visual Semantic Segmentation for Autonomous Driving—0
eDifFIQA: Towards Efficient Face Image Quality Assessment Based On Denoising Diffusion Probabilistic ModelsCode1
Low-Energy On-Device Personalization for MCUsCode0
CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-TuningCode2
Continual All-in-One Adverse Weather Removal with Knowledge Replay on a Unified Network StructureCode1
Distilling the Knowledge in Data Pruning—0
Enhancing Adversarial Training with Prior Knowledge Distillation for Robust Image Compression—0
Evolving Knowledge Distillation with Large Language Models and Active Learning—0
AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge DistillationCode0
One Category One Prompt: Dataset Distillation using Diffusion Models—0
Enhanced Sparsification via Stimulative Training—0
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All datasetsImageNetCIFAR-100COCO (Common Objects in Context)COCO 2017 valPASCAL VOCKITTI

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ScaleKD (T:BEiT-L S:ViT-B/14)Top-1 accuracy %86.43—Unverified
2ScaleKD (T:Swin-L S:ViT-B/16)Top-1 accuracy %85.53—Unverified
3ScaleKD (T:Swin-L S:ViT-S/16)Top-1 accuracy %83.93—Unverified
4ScaleKD (T:Swin-L S:Swin-T)Top-1 accuracy %83.8—Unverified
5KD++(T: regnety-16GF S:ViT-B)Top-1 accuracy %83.6—Unverified
6VkD (T:RegNety 160 S:DeiT-S)Top-1 accuracy %82.9—Unverified
7SpectralKD (T:Swin-S S:Swin-T)Top-1 accuracy %82.7—Unverified
8ScaleKD (T:Swin-L S:ResNet-50)Top-1 accuracy %82.55—Unverified
9DiffKD (T:Swin-L S: Swin-T)Top-1 accuracy %82.5—Unverified
10DIST (T: Swin-L S: Swin-T)Top-1 accuracy %82.3—Unverified
#ModelMetricClaimedVerifiedStatus
1SRD (T:resnet-32x4, S:shufflenet-v2)Top-1 Accuracy (%)79.86—Unverified
2shufflenet-v2(T:resnet-32x4, S:shufflenet-v2)Top-1 Accuracy (%)78.76—Unverified
3MV-MR (T: CLIP/ViT-B-16 S: resnet50)Top-1 Accuracy (%)78.6—Unverified
4resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)78.28—Unverified
5resnet8x4 (T: resnet32x4 S: resnet8x4 [modified])Top-1 Accuracy (%)78.08—Unverified
6ReviewKD++(T:resnet-32x4, S:shufflenet-v2)Top-1 Accuracy (%)77.93—Unverified
7ReviewKD++(T:resnet-32x4, S:shufflenet-v1)Top-1 Accuracy (%)77.68—Unverified
8resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)77.5—Unverified
9resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)76.68—Unverified
10resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)76.31—Unverified
#ModelMetricClaimedVerifiedStatus
1LSHFM (T: ResNet101 S: ResNet50)mAP77.16—Unverified
2LSHFM (T: ResNet101 S: MobileNetV2)mAP73.73—Unverified
3ADLIK-Faster (T: Faster R-CNN vit-base S: Faster R-CNN deit-small) box AP47.6—Unverified
4ADLIK-Mask (T: Mask R-CNN vit-base S: Mask R-CNN deit-small)mask AP42.4—Unverified
#ModelMetricClaimedVerifiedStatus
1ReviewKD++(T: faster rcnn(resnet101), S:faster rcnn(resnet50))AP@0.561.8—Unverified
2ReviewKD++(T: faster rcnn(resnet101), S:faster rcnn(resnet18))AP@0.557.96—Unverified
3ReviewKD++(T: faster rcnn(resnet101), S:faster rcnn(mobilenet-v2))AP@0.555.18—Unverified
#ModelMetricClaimedVerifiedStatus
1LSHFM (T: ResNet101 S: ResNet50)mAP93.17—Unverified
2LSHFM (T: ResNet101 S: MobileNetV2)mAP90.14—Unverified
#ModelMetricClaimedVerifiedStatus
1TIE-KD (T: Adabins S: MobileNetV2)RMSE2.43—Unverified