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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 551–600 of 4240 papers

TitleStatusHype
Consensual Collaborative Training And Knowledge Distillation Based Facial Expression Recognition Under Noisy AnnotationsCode1
ConStyle v2: A Strong Prompter for All-in-One Image RestorationCode1
Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image ClassificationCode1
Consistent Representation Learning for Continual Relation ExtractionCode1
Anti-Distillation Backdoor Attacks: Backdoors Can Really Survive in Knowledge DistillationCode1
Designing Large Foundation Models for Efficient Training and Inference: A SurveyCode1
Context-Aware Image Inpainting with Learned Semantic PriorsCode1
Content-Variant Reference Image Quality Assessment via Knowledge DistillationCode1
FedCL: Federated Multi-Phase Curriculum Learning to Synchronously Correlate User HeterogeneityCode1
CCL: Continual Contrastive Learning for LiDAR Place RecognitionCode1
Continual evaluation for lifelong learning: Identifying the stability gapCode1
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated LearningCode1
Continual Learning for LiDAR Semantic Segmentation: Class-Incremental and Coarse-to-Fine strategies on Sparse DataCode1
Continual Learning for Image Segmentation with Dynamic QueryCode1
CEKD: Cross-Modal Edge-Privileged Knowledge Distillation for Semantic Scene Understanding Using Only Thermal ImagesCode1
CEN-HDR: Computationally Efficient neural Network for real-time High Dynamic Range imagingCode1
A Dual-Space Framework for General Knowledge Distillation of Large Language ModelsCode1
Contrastive Deep SupervisionCode1
Contrastive Distillation on Intermediate Representations for Language Model CompressionCode1
Channel-Aware Distillation Transformer for Depth Estimation on Nano DronesCode1
Channel Distillation: Channel-Wise Attention for Knowledge DistillationCode1
Contrastive Representation DistillationCode1
Channel Gating Neural NetworksCode1
FedX: Unsupervised Federated Learning with Cross Knowledge DistillationCode1
FitNets: Hints for Thin Deep NetsCode1
Exploring Performance-Complexity Trade-Offs in Sound Event Detection ModelsCode1
Cumulative Spatial Knowledge Distillation for Vision TransformersCode1
CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray SegmentationCode1
Chinese grammatical error correction based on knowledge distillationCode1
Complementary Relation Contrastive DistillationCode1
Circumventing Outliers of AutoAugment with Knowledge DistillationCode1
CrossKD: Cross-Head Knowledge Distillation for Object DetectionCode1
Cross-Modal Fusion Distillation for Fine-Grained Sketch-Based Image RetrievalCode1
CTC-based Non-autoregressive Textless Speech-to-Speech TranslationCode1
Cross-modality Data Augmentation for End-to-End Sign Language TranslationCode1
Class Attention Transfer Based Knowledge DistillationCode1
Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly DetectionCode1
Class-Balanced Distillation for Long-Tailed Visual RecognitionCode1
CSAKD: Knowledge Distillation with Cross Self-Attention for Hyperspectral and Multispectral Image FusionCode1
Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation FrameworkCode1
APSNet: Attention Based Point Cloud SamplingCode1
Curriculum Learning for Dense Retrieval DistillationCode1
Advantage-Guided Distillation for Preference Alignment in Small Language ModelsCode1
Curriculum Temperature for Knowledge DistillationCode1
3D Annotation-Free Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous DrivingCode1
Generative Model-based Feature Knowledge Distillation for Action RecognitionCode1
Class-Incremental Learning by Knowledge Distillation with Adaptive Feature ConsolidationCode1
GenFormer -- Generated Images are All You Need to Improve Robustness of Transformers on Small DatasetsCode1
Are Intermediate Layers and Labels Really Necessary? A General Language Model Distillation MethodCode1
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge DistillationCode1
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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