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 401–450 of 4240 papers

TitleStatusHype
Backdoor Attacks on Self-Supervised LearningCode1
Backdoor Cleansing with Unlabeled DataCode1
A semi-supervised Teacher-Student framework for surgical tool detection and localizationCode1
End-to-End Zero-Shot HOI Detection via Vision and Language Knowledge DistillationCode1
Enhancing and Adapting in the Clinic: Source-free Unsupervised Domain Adaptation for Medical Image EnhancementCode1
Enhancing Cross-Tokenizer Knowledge Distillation with Contextual Dynamical MappingCode1
Cross-Layer Distillation with Semantic CalibrationCode1
Action knowledge for video captioning with graph neural networksCode1
CrossKD: Cross-Head Knowledge Distillation for Object DetectionCode1
Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot ClassificationCode1
Curriculum Learning for Dense Retrieval DistillationCode1
Even your Teacher Needs Guidance: Ground-Truth Targets Dampen Regularization Imposed by Self-DistillationCode1
Aligned Structured Sparsity Learning for Efficient Image Super-ResolutionCode1
Expanding Scene Graph Boundaries: Fully Open-vocabulary Scene Graph Generation via Visual-Concept Alignment and RetentionCode1
Bayes Conditional Distribution Estimation for Knowledge Distillation Based on Conditional Mutual InformationCode1
C2KD: Cross-Lingual Cross-Modal Knowledge Distillation for Multilingual Text-Video RetrievalCode1
Exploring Performance-Complexity Trade-Offs in Sound Event Detection ModelsCode1
BearingPGA-Net: A Lightweight and Deployable Bearing Fault Diagnosis Network via Decoupled Knowledge Distillation and FPGA AccelerationCode1
DA-Mamba: Domain Adaptive Hybrid Mamba-Transformer Based One-Stage Object DetectionCode1
FAMIE: A Fast Active Learning Framework for Multilingual Information ExtractionCode1
Faster ILOD: Incremental Learning for Object Detectors based on Faster RCNNCode1
FastFormers: Highly Efficient Transformer Models for Natural Language UnderstandingCode1
Align-KD: Distilling Cross-Modal Alignment Knowledge for Mobile Vision-Language ModelCode1
FCS: Feature Calibration and Separation for Non-Exemplar Class Incremental LearningCode1
BERT-of-Theseus: Compressing BERT by Progressive Module ReplacingCode1
Align-KD: Distilling Cross-Modal Alignment Knowledge for Mobile Vision-Language Large Model EnhancementCode1
Better Estimation of the KL Divergence Between Language ModelsCode1
Fcaformer: Forward Cross Attention in Hybrid Vision TransformerCode1
FedCL: Federated Multi-Phase Curriculum Learning to Synchronously Correlate User HeterogeneityCode1
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated LearningCode1
Adjoined Networks: A Training Paradigm with Applications to Network CompressionCode1
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object DetectionCode1
BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object DetectionCode1
SimDistill: Simulated Multi-modal Distillation for BEV 3D Object DetectionCode1
FedMD: Heterogenous Federated Learning via Model DistillationCode1
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise HeterogeneityCode1
Beyond Generic: Enhancing Image Captioning with Real-World Knowledge using Vision-Language Pre-Training ModelCode1
Beyond Preserved Accuracy: Evaluating Loyalty and Robustness of BERT CompressionCode1
Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve BackbonesCode1
AlphaFold Distillation for Protein DesignCode1
Contrastive Distillation on Intermediate Representations for Language Model CompressionCode1
Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated LearningCode1
CaMEL: Mean Teacher Learning for Image CaptioningCode1
Fitting Auditory Filterbanks with Multiresolution Neural NetworksCode1
Contrastive Deep SupervisionCode1
AltDiffusion: A Multilingual Text-to-Image Diffusion ModelCode1
Bidirectional Distillation for Top-K Recommender SystemCode1
Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image ClassificationCode1
Contrastive Model Inversion for Data-Free Knowledge DistillationCode1
Are Intermediate Layers and Labels Really Necessary? A General Language Model Distillation MethodCode1
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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))[email protected]61.8—Unverified
2ReviewKD++(T: faster rcnn(resnet101), S:faster rcnn(resnet18))[email protected]57.96—Unverified
3ReviewKD++(T: faster rcnn(resnet101), S:faster rcnn(mobilenet-v2))[email protected]55.18—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