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 37263750 of 4240 papers

TitleStatusHype
Multi-Frame to Single-Frame: Knowledge Distillation for 3D Object Detection0
Open-set Short Utterance Forensic Speaker Verification using Teacher-Student Network with Explicit Inductive Bias0
EI-MTD:Moving Target Defense for Edge Intelligence against Adversarial Attacks0
Weight Distillation: Transferring the Knowledge in Neural Network Parameters0
Introspective Learning by Distilling Knowledge from Online Self-explanation0
Densely Guided Knowledge Distillation using Multiple Teacher AssistantsCode1
Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning0
MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without TricksCode1
S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric LearningCode1
Mimic and Conquer: Heterogeneous Tree Structure Distillation for Syntactic NLP0
Simplified TinyBERT: Knowledge Distillation for Document RetrievalCode1
Noisy Self-Knowledge Distillation for Text SummarizationCode1
Collaborative Distillation in the Parameter and Spectrum Domains for Video Action Recognition0
Autoregressive Knowledge Distillation through Imitation LearningCode0
SSKD: Self-Supervised Knowledge Distillation for Cross Domain Adaptive Person Re-Identification0
BoostingBERT:Integrating Multi-Class Boosting into BERT for NLP Tasks0
DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning0
Extending Label Smoothing Regularization with Self-Knowledge Distillation0
On the Orthogonality of Knowledge Distillation with Other Techniques: From an Ensemble Perspective0
Simulating Unknown Target Models for Query-Efficient Black-box AttacksCode1
SAIL: Self-Augmented Graph Contrastive Learning0
Lifelong Object Detection0
Classification of Diabetic Retinopathy Using Unlabeled Data and Knowledge Distillation0
Semantics-aware Adaptive Knowledge Distillation for Sensor-to-Vision Action RecognitionCode1
Automatic Assignment of Radiology Examination Protocols Using Pre-trained Language Models with Knowledge DistillationCode0
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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