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 1151–1200 of 4240 papers

TitleStatusHype
A Knowledge Distillation Ensemble Framework for Predicting Short and Long-term Hospitalisation Outcomes from Electronic Health Records DataCode0
Knowledge Extraction with No Observable DataCode0
KnowledgeSG: Privacy-Preserving Synthetic Text Generation with Knowledge Distillation from ServerCode0
Autoregressive Knowledge Distillation through Imitation LearningCode0
Knowledge Distillation with Adversarial Samples Supporting Decision BoundaryCode0
Correlation Congruence for Knowledge DistillationCode0
TextKD-GAN: Text Generation using KnowledgeDistillation and Generative Adversarial NetworksCode0
Knowledge distillation to effectively attain both region-of-interest and global semantics from an image where multiple objects appearCode0
A Knowledge Distillation-Based Approach to Enhance Transparency of Classifier ModelsCode0
CoReD: Generalizing Fake Media Detection with Continual Representation using DistillationCode0
Automatic Assignment of Radiology Examination Protocols Using Pre-trained Language Models with Knowledge DistillationCode0
Knowledge Distillation via Instance Relationship GraphCode0
Knowledge Distillation with Reptile Meta-Learning for Pretrained Language Model CompressionCode0
Cooperative Retriever and Ranker in Deep RecommendersCode0
Automatic adaptation of object detectors to new domains using self-trainingCode0
Cooperative Knowledge Distillation: A Learner Agnostic ApproachCode0
Automated Knowledge Distillation via Monte Carlo Tree SearchCode0
Knowledge Distillation of Russian Language Models with Reduction of VocabularyCode0
Cooperative Classification and Rationalization for Graph GeneralizationCode0
Knowledge Distillation Layer that Lets the Student DecideCode0
Knowledge Distillation in RNN-Attention Models for Early Prediction of Student PerformanceCode0
Knowledge Distillation Performs Partial Variance ReductionCode0
On the Byzantine-Resilience of Distillation-Based Federated LearningCode0
Knowledge Distillation for Quality EstimationCode0
Knowledge Distillation for Singing Voice DetectionCode0
Knowledge Distillation for Multi-Target Domain Adaptation in Real-Time Person Re-IdentificationCode0
Knowledge Distillation For Wireless Edge LearningCode0
Contrastive Learning in Distilled ModelsCode0
Knowledge Distillation for Detection Transformer with Consistent Distillation Points SamplingCode0
Knowledge Distillation for End-to-End Person SearchCode0
MiniDisc: Minimal Distillation Schedule for Language Model CompressionCode0
Knowledge Distillation By Sparse Representation MatchingCode0
Contrastive Conditioning for Assessing Disambiguation in MT: A Case Study of Distilled BiasCode0
Knowledge Distillation by On-the-Fly Native EnsembleCode0
AI-KD: Towards Alignment Invariant Face Image Quality Assessment Using Knowledge DistillationCode0
Knowledge Distillation-Based Model Extraction Attack using GAN-based Private Counterfactual ExplanationsCode0
A Unified Object Counting Network with Object Occupation PriorCode0
Knowledge Distillation as Semiparametric InferenceCode0
Continual Representation Learning for Biometric IdentificationCode0
Continual Panoptic Perception: Towards Multi-modal Incremental Interpretation of Remote Sensing ImagesCode0
Continual Knowledge Distillation for Neural Machine TranslationCode0
KD-VLP: Improving End-to-End Vision-and-Language Pretraining with Object Knowledge DistillationCode0
Leveraging Entity Information for Cross-Modality Correlation Learning: The Entity-Guided Multimodal SummarizationCode0
Joint Progressive Knowledge Distillation and Unsupervised Domain AdaptationCode0
Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge GraphsCode0
KDMOS:Knowledge Distillation for Motion SegmentationCode0
Knowledge Distillation approach towards Melanoma DetectionCode0
Continual Contrastive Learning for Image ClassificationCode0
Continual Coarse-to-Fine Domain Adaptation in Semantic SegmentationCode0
AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge DistillationCode0
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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