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

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Showing 3751–3800 of 4240 papers

TitleStatusHype
Initial Classifier Weights Replay for Memoryless Class Incremental Learning—0
Unpaired Learning of Deep Image DenoisingCode1
MetaDistiller: Network Self-Boosting via Meta-Learned Top-Down Distillation—0
Performance Optimization for Federated Person Re-identification via Benchmark AnalysisCode1
Point Adversarial Self Mining: A Simple Method for Facial Expression Recognition—0
Active Class Incremental Learning for Imbalanced Datasets—0
Multi-Person Full Body Pose Estimation—0
Learn to Talk via Proactive Knowledge Transfer—0
Rectified Decision Trees: Exploring the Landscape of Interpretable and Effective Machine Learning—0
Learning to Extract Attribute Value from Product via Question Answering: A Multi-task Approach—0
PARADE: Passage Representation Aggregation for Document RerankingCode1
Knowledge Transfer via Dense Cross-Layer Mutual-DistillationCode1
Cascaded channel pruning using hierarchical self-distillation—0
An Ensemble of Knowledge Sharing Models for Dynamic Hand Gesture Recognition—0
Compression of Deep Learning Models for Text: A Survey—0
Towards Unsupervised Crowd Counting via Regression-Detection Bi-knowledge Transfer—0
Compact Speaker Embedding: lrx-vector—0
S2OSC: A Holistic Semi-Supervised Approach for Open Set Classification—0
Knowledge Distillation-aided End-to-End Learning for Linear Precoding in Multiuser MIMO Downlink Systems with Finite-Rate Feedback—0
Knowledge Distillation and Data Selection for Semi-Supervised Learning in CTC Acoustic Models—0
Distilling the Knowledge of BERT for Sequence-to-Sequence ASRCode1
LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition—0
MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models—0
Prime-Aware Adaptive Distillation—0
TutorNet: Towards Flexible Knowledge Distillation for End-to-End Speech Recognition—0
Teacher-Student Training and Triplet Loss for Facial Expression Recognition under Occlusion—0
Differentiable Feature Aggregation Search for Knowledge Distillation—0
Weight Decay Scheduling and Knowledge Distillation for Active Learning—0
Improving Knowledge Distillation via Category StructureCode1
Exclusivity-Consistency Regularized Knowledge Distillation for Face Recognition—0
Feature Normalized Knowledge Distillation for Image ClassificationCode0
Local Correlation Consistency for Knowledge Distillation—0
Intra-class Feature Variation Distillation for Semantic SegmentationCode1
YOLO in the Dark - Domain Adaptation Method for Merging Multiple Models -—0
AMLN: Adversarial-based Mutual Learning Network for Online Knowledge Distillation—0
Distilling Visual Priors from Self-Supervised LearningCode1
Group Knowledge Transfer: Federated Learning of Large CNNs at the EdgeCode1
Weakly Supervised 3D Object Detection from Point CloudsCode1
Dynamic Knowledge Distillation for Black-box Hypothesis Transfer Learning—0
Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance SegmentationCode1
Interpretable Foreground Object Search As Knowledge Distillation—0
Multi-label Contrastive Predictive Coding—0
Resolution Switchable Networks for Runtime Efficient Image RecognitionCode1
Knowledge Distillation in Deep Learning and its Applications—0
CovidCare: Transferring Knowledge from Existing EMR to Emerging Epidemic for Interpretable Prognosis—0
Defocus Blur Detection via Depth DistillationCode1
Self-supervision on Unlabelled OR Data for Multi-person 2D/3D Human Pose EstimationCode1
UniTrans: Unifying Model Transfer and Data Transfer for Cross-Lingual Named Entity Recognition with Unlabeled DataCode0
Add a SideNet to your MainNet—0
P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection—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