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 3751–3800 of 4240 papers

TitleStatusHype
Just KIDDIN: Knowledge Infusion and Distillation for Detection of INdecent Memes—0
K-AID: Enhancing Pre-trained Language Models with Domain Knowledge for Question Answering—0
KAT-V1: Kwai-AutoThink Technical Report—0
KD^2M: An unifying framework for feature knowledge distillation—0
KDC-MAE: Knowledge Distilled Contrastive Mask Auto-Encoder—0
KDCTime: Knowledge Distillation with Calibration on InceptionTime for Time-series Classification—0
KD-DETR: Knowledge Distillation for Detection Transformer with Consistent Distillation Points Sampling—0
KD-DLGAN: Data Limited Image Generation via Knowledge Distillation—0
KDExplainer: A Task-oriented Attention Model for Explaining Knowledge Distillation—0
KD-FixMatch: Knowledge Distillation Siamese Neural Networks—0
KDGAN: Knowledge Distillation with Generative Adversarial Networks—0
KDH-MLTC: Knowledge Distillation for Healthcare Multi-Label Text Classification—0
KDk: A Defense Mechanism Against Label Inference Attacks in Vertical Federated Learning—0
KDLSQ-BERT: A Quantized Bert Combining Knowledge Distillation with Learned Step Size Quantization—0
KDRL: Post-Training Reasoning LLMs via Unified Knowledge Distillation and Reinforcement Learning—0
KDSM: An uplift modeling framework based on knowledge distillation and sample matching—0
KDSTM: Neural Semi-supervised Topic Modeling with Knowledge Distillation—0
KD-VLP: Improving End-to-End Vision-and-Language Pretraining with Object Knowledge Distillation—0
Keep Decoding Parallel with Effective Knowledge Distillation from Language Models to End-to-end Speech Recognisers—0
Kendall's τ Coefficient for Logits Distillation—0
Kernel Based Progressive Distillation for Adder Neural Networks—0
Kernel Methods in Hyperbolic Spaces—0
KEYword based Sampling (KEYS) for Large Language Models—0
KGEx: Explaining Knowledge Graph Embeddings via Subgraph Sampling and Knowledge Distillation—0
Enhancing CLIP Conceptual Embedding through Knowledge Distillation—0
KnFu: Effective Knowledge Fusion—0
KNIFE: Distilling Reasoning Knowledge From Free-Text Rationales—0
Knowledge Adaptation for Efficient Semantic Segmentation—0
Knowledge Adaptation: Teaching to Adapt—0
Knowledge as Priors: Cross-Modal Knowledge Generalization for Datasets without Superior Knowledge—0
Knowledge Concentration: Learning 100K Object Classifiers in a Single CNN—0
Knowledge Cross-Distillation for Membership Privacy—0
Knowledge Distillation and Data Selection for Semi-Supervised Learning in CTC Acoustic Models—0
Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions—0
Knowledge Distillation and Enhanced Subdomain Adaptation Using Graph Convolutional Network for Resource-Constrained Bearing Fault Diagnosis—0
Knowledge Distillation Applied to Optical Channel Equalization: Solving the Parallelization Problem of Recurrent Connection—0
Knowledge Distillation Label Smoothing: Fact or Fallacy?—0
Knowledge Distillation as Self-Supervised Learning—0
Knowledge Distillation: A Survey—0
Knowledge Distillation: Bad Models Can Be Good Role Models—0
Knowledge Distillation based Contextual Relevance Matching for E-commerce Product Search—0
Knowledge Distillation based Ensemble Learning for Neural Machine Translation—0
Knowledge Distillation-based Information Sharing for Online Process Monitoring in Decentralized Manufacturing System—0
Knowledge Distillation Based Semantic Communications For Multiple Users—0
Knowledge Distillation Beyond Model Compression—0
Knowledge Distillation Circumvents Nonlinearity for Optical Convolutional Neural Networks—0
Knowledge Distillation-Empowered Digital Twin for Anomaly Detection—0
Knowledge Distillation for 6D Pose Estimation by Aligning Distributions of Local Predictions—0
Knowledge Distillation for Action Anticipation via Label Smoothing—0
Knowledge Distillation for Adaptive MRI Prostate Segmentation Based on Limit-Trained Multi-Teacher Models—0
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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