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

Showing 25762600 of 4240 papers

TitleStatusHype
PGX: A Multi-level GNN Explanation Framework Based on Separate Knowledge Distillation Processes0
Distributional Correlation--Aware Knowledge Distillation for Stock Trading Volume PredictionCode1
Deep Semi-Supervised and Self-Supervised Learning for Diabetic Retinopathy Detection0
KD-SCFNet: Towards More Accurate and Efficient Salient Object Detection via Knowledge DistillationCode1
Pose Uncertainty Aware Movement Synchrony Estimation via Spatial-Temporal Graph Transformer0
Generative Bias for Robust Visual Question AnsweringCode1
Chinese grammatical error correction based on knowledge distillationCode1
Aggretriever: A Simple Approach to Aggregate Textual Representations for Robust Dense Passage RetrievalCode1
SDBERT: SparseDistilBERT, a faster and smaller BERT model0
Meta-Learning based Degradation Representation for Blind Super-ResolutionCode1
NICEST: Noisy Label Correction and Training for Robust Scene Graph Generation0
Exploring Generalizable Distillation for Efficient Medical Image SegmentationCode0
HIRE: Distilling High-order Relational Knowledge From Heterogeneous Graph Neural Networks0
Domain-invariant Feature Exploration for Domain Generalization0
Black-box Few-shot Knowledge DistillationCode1
Few-Shot Object Detection by Knowledge Distillation Using Bag-of-Visual-Words Representations0
Spatial-Channel Token Distillation for Vision MLPsCode0
Handling Data Heterogeneity in Federated Learning via Knowledge Distillation and FusionCode0
Online Knowledge Distillation via Mutual Contrastive Learning for Visual RecognitionCode1
Hyper-Representations for Pre-Training and Transfer LearningCode1
Few-Shot Class-Incremental Learning via Entropy-Regularized Data-Free ReplayCode0
Federated Semi-Supervised Domain Adaptation via Knowledge Transfer0
TinyViT: Fast Pretraining Distillation for Small Vision Transformers0
KD-MVS: Knowledge Distillation Based Self-supervised Learning for Multi-view StereoCode1
Many-to-One Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Internet of Things Systems0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ScaleKD (T:BEiT-L S:ViT-B/14)Top-1 accuracy %86.43Unverified
2ScaleKD (T:Swin-L S:ViT-B/16)Top-1 accuracy %85.53Unverified
3ScaleKD (T:Swin-L S:ViT-S/16)Top-1 accuracy %83.93Unverified
4ScaleKD (T:Swin-L S:Swin-T)Top-1 accuracy %83.8Unverified
5KD++(T: regnety-16GF S:ViT-B)Top-1 accuracy %83.6Unverified
6VkD (T:RegNety 160 S:DeiT-S)Top-1 accuracy %82.9Unverified
7SpectralKD (T:Swin-S S:Swin-T)Top-1 accuracy %82.7Unverified
8ScaleKD (T:Swin-L S:ResNet-50)Top-1 accuracy %82.55Unverified
9DiffKD (T:Swin-L S: Swin-T)Top-1 accuracy %82.5Unverified
10DIST (T: Swin-L S: Swin-T)Top-1 accuracy %82.3Unverified
#ModelMetricClaimedVerifiedStatus
1SRD (T:resnet-32x4, S:shufflenet-v2)Top-1 Accuracy (%)79.86Unverified
2shufflenet-v2(T:resnet-32x4, S:shufflenet-v2)Top-1 Accuracy (%)78.76Unverified
3MV-MR (T: CLIP/ViT-B-16 S: resnet50)Top-1 Accuracy (%)78.6Unverified
4resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)78.28Unverified
5resnet8x4 (T: resnet32x4 S: resnet8x4 [modified])Top-1 Accuracy (%)78.08Unverified
6ReviewKD++(T:resnet-32x4, S:shufflenet-v2)Top-1 Accuracy (%)77.93Unverified
7ReviewKD++(T:resnet-32x4, S:shufflenet-v1)Top-1 Accuracy (%)77.68Unverified
8resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)77.5Unverified
9resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)76.68Unverified
10resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)76.31Unverified
#ModelMetricClaimedVerifiedStatus
1LSHFM (T: ResNet101 S: ResNet50)mAP93.17Unverified
2LSHFM (T: ResNet101 S: MobileNetV2)mAP90.14Unverified
#ModelMetricClaimedVerifiedStatus
1TIE-KD (T: Adabins S: MobileNetV2)RMSE2.43Unverified