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 1201–1250 of 4240 papers

TitleStatusHype
Knowledge Distillation in RNN-Attention Models for Early Prediction of Student PerformanceCode0
Few Sample Knowledge Distillation for Efficient Network CompressionCode0
Accelerated Proton Resonance Frequency-based Magnetic Resonance Thermometry by Optimized Deep Learning MethodCode0
Knowledge Distillation from Single to Multi Labels: an Empirical StudyCode0
Knowledge Distillation Layer that Lets the Student DecideCode0
AttriPrompter: Auto-Prompting with Attribute Semantics for Zero-shot Nuclei Detection via Visual-Language Pre-trained ModelsCode0
Content Based Singing Voice Extraction From a Musical MixtureCode0
Attentive Task Interaction Network for Multi-Task LearningCode0
AdaGMLP: AdaBoosting GNN-to-MLP Knowledge DistillationCode0
Knowledge Distillation from Cross Teaching Teachers for Efficient Semi-Supervised Abdominal Organ Segmentation in CTCode0
Knowledge Distillation for Singing Voice DetectionCode0
Attention to detail: inter-resolution knowledge distillationCode0
Knowledge Distillation for End-to-End Person SearchCode0
Knowledge Distillation for Multi-Target Domain Adaptation in Real-Time Person Re-IdentificationCode0
Knowledge Distillation for Quality EstimationCode0
Knowledge Distillation For Wireless Edge LearningCode0
Knowledge Distillation By Sparse Representation MatchingCode0
Knowledge Distillation by On-the-Fly Native EnsembleCode0
Knowledge Distillation-Based Model Extraction Attack using GAN-based Private Counterfactual ExplanationsCode0
CONetV2: Efficient Auto-Channel Size Optimization for CNNsCode0
Knowledge Distillation as Semiparametric InferenceCode0
Knowledge Distillation for Detection Transformer with Consistent Distillation Points SamplingCode0
Attention-Based Depth Distillation with 3D-Aware Positional Encoding for Monocular 3D Object DetectionCode0
Attend, Distill, Detect: Attention-aware Entropy Distillation for Anomaly DetectionCode0
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture SearchCode0
KD-VLP: Improving End-to-End Vision-and-Language Pretraining with Object Knowledge DistillationCode0
ACT-Net: Asymmetric Co-Teacher Network for Semi-supervised Memory-efficient Medical Image SegmentationCode0
Is Smaller Always Faster? Tradeoffs in Compressing Self-Supervised Speech TransformersCode0
Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge GraphsCode0
A Teacher-Free Graph Knowledge Distillation Framework with Dual Self-DistillationCode0
Joint Progressive Knowledge Distillation and Unsupervised Domain AdaptationCode0
A Tailored Pre-Training Model for Task-Oriented Dialog GenerationCode0
KDMOS:Knowledge Distillation for Motion SegmentationCode0
A Systematic Study of Knowledge Distillation for Natural Language Generation with Pseudo-Target TrainingCode0
Is Modularity Transferable? A Case Study through the Lens of Knowledge DistillationCode0
Complex Facial Expression Recognition Using Deep Knowledge Distillation of Basic FeaturesCode0
Comb, Prune, Distill: Towards Unified Pruning for Vision Model CompressionCode0
Invariant debiasing learning for recommendation via biased imputationCode0
Joint Answering and Explanation for Visual Commonsense ReasoningCode0
Asymmetric Masked Distillation for Pre-Training Small Foundation ModelsCode0
Intra-class Patch Swap for Self-DistillationCode0
Active Object Detection with Knowledge Aggregation and Distillation from Large ModelsCode0
Complementary Calibration: Boosting General Continual Learning with Collaborative Distillation and Self-SupervisionCode0
Interpreting Microbiome Relative Abundance Data Using Symbolic RegressionCode0
Interpreting and Disentangling Feature Components of Various Complexity from DNNsCode0
Comparative Knowledge DistillationCode0
Compact Trilinear Interaction for Visual Question AnsweringCode0
Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical DiagnosisCode0
Instance Temperature Knowledge DistillationCode0
Infusing Sequential Information into Conditional Masked Translation Model with Self-Review MechanismCode0
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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