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 25512575 of 4240 papers

TitleStatusHype
RAIN: RegulArization on Input and Network for Black-Box Domain AdaptationCode0
Multi-Granularity Distillation Scheme Towards Lightweight Semi-Supervised Semantic SegmentationCode1
LTE4G: Long-Tail Experts for Graph Neural NetworksCode1
Rethinking Knowledge Distillation via Cross-Entropy0
Multi-View Attention Transfer for Efficient Speech Enhancement0
A semi-supervised Teacher-Student framework for surgical tool detection and localizationCode1
Combining Compressions for Multiplicative Size Scaling on Natural Language Tasks0
Effectiveness of Function Matching in Driving Scene Recognition0
Mind the Gap in Distilling StyleGANsCode1
Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification0
Leukocyte Classification using Multimodal Architecture Enhanced by Knowledge Distillation0
Progressive Cross-modal Knowledge Distillation for Human Action Recognition0
Unsupervised Domain Adaptation for Segmentation with Black-box Source Model0
Enhancing Heterogeneous Federated Learning with Knowledge Extraction and Multi-Model FusionCode0
RAWtoBit: A Fully End-to-end Camera ISP Network0
BEiT v2: Masked Image Modeling with Vector-Quantized Visual TokenizersCode0
Non-Autoregressive Sign Language Production via Knowledge Distillation0
A Knowledge Distillation-Based Backdoor Attack in Federated Learning0
MixSKD: Self-Knowledge Distillation from Mixup for Image RecognitionCode1
Self-Knowledge Distillation via Dropout0
PA-Seg: Learning from Point Annotations for 3D Medical Image Segmentation using Contextual Regularization and Cross Knowledge DistillationCode1
SKDCGN: Source-free Knowledge Distillation of Counterfactual Generative Networks using cGANsCode0
Study of Encoder-Decoder Architectures for Code-Mix Search Query Translation0
Label Semantic Knowledge Distillation for Unbiased Scene Graph Generation0
Task-Balanced Distillation for Object Detection0
Show:102550
← PrevPage 103 of 170Next →

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