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

Showing 30263050 of 4240 papers

TitleStatusHype
Cross-Lingual NER for Financial Transaction Data in Low-Resource Languages0
Cross-modal Contrastive Distillation for Instructional Activity Anticipation0
Cross Modal Distillation for Flood Extent Mapping0
Cross-modal knowledge distillation for action recognition0
Crossmodal Knowledge Distillation with WordNet-Relaxed Text Embeddings for Robust Image Classification0
Cross-Resolution Face Recognition via Prior-Aided Face Hallucination and Residual Knowledge Distillation0
Canine EEG Helps Human: Cross-Species and Cross-Modality Epileptic Seizure Detection via Multi-Space Alignment0
Cross-Task Knowledge Distillation in Multi-Task Recommendation0
Crowd Counting with Online Knowledge Learning0
CTC Blank Triggered Dynamic Layer-Skipping for Efficient CTC-based Speech Recognition0
CULL-MT: Compression Using Language and Layer pruning for Machine Translation0
CustomKD: Customizing Large Vision Foundation for Edge Model Improvement via Knowledge Distillation0
D^3ETR: Decoder Distillation for Detection Transformer0
D3T-GAN: Data-Dependent Domain Transfer GANs for Few-shot Image Generation0
DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection0
DaFKD: Domain-Aware Federated Knowledge Distillation0
DAKD: Data Augmentation and Knowledge Distillation using Diffusion Models for SAR Oil Spill Segmentation0
DASECount: Domain-Agnostic Sample-Efficient Wireless Indoor Crowd Counting via Few-shot Learning0
Data-Driven Compression of Convolutional Neural Networks0
Data Efficient Acoustic Scene Classification using Teacher-Informed Confusing Class Instruction0
Data-efficient Event Camera Pre-training via Disentangled Masked Modeling0
Data-Efficient Ranking Distillation for Image Retrieval0
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks0
Dense Depth Distillation with Out-of-Distribution Simulated Images0
Data-Free Distillation of Language Model by Text-to-Text Transfer0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ScaleKD (T:BEiT-L S:ViT-B/14)Top-1 accuracy %86.43Unverified
2ScaleKD (T:Swin-L S:ViT-B/16)Top-1 accuracy %85.53Unverified
3ScaleKD (T:Swin-L S:ViT-S/16)Top-1 accuracy %83.93Unverified
4ScaleKD (T:Swin-L S:Swin-T)Top-1 accuracy %83.8Unverified
5KD++(T: regnety-16GF S:ViT-B)Top-1 accuracy %83.6Unverified
6VkD (T:RegNety 160 S:DeiT-S)Top-1 accuracy %82.9Unverified
7SpectralKD (T:Swin-S S:Swin-T)Top-1 accuracy %82.7Unverified
8ScaleKD (T:Swin-L S:ResNet-50)Top-1 accuracy %82.55Unverified
9DiffKD (T:Swin-L S: Swin-T)Top-1 accuracy %82.5Unverified
10DIST (T: Swin-L S: Swin-T)Top-1 accuracy %82.3Unverified
#ModelMetricClaimedVerifiedStatus
1SRD (T:resnet-32x4, S:shufflenet-v2)Top-1 Accuracy (%)79.86Unverified
2shufflenet-v2(T:resnet-32x4, S:shufflenet-v2)Top-1 Accuracy (%)78.76Unverified
3MV-MR (T: CLIP/ViT-B-16 S: resnet50)Top-1 Accuracy (%)78.6Unverified
4resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)78.28Unverified
5resnet8x4 (T: resnet32x4 S: resnet8x4 [modified])Top-1 Accuracy (%)78.08Unverified
6ReviewKD++(T:resnet-32x4, S:shufflenet-v2)Top-1 Accuracy (%)77.93Unverified
7ReviewKD++(T:resnet-32x4, S:shufflenet-v1)Top-1 Accuracy (%)77.68Unverified
8resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)77.5Unverified
9resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)76.68Unverified
10resnet8x4 (T: resnet32x4 S: resnet8x4)Top-1 Accuracy (%)76.31Unverified
#ModelMetricClaimedVerifiedStatus
1LSHFM (T: ResNet101 S: ResNet50)mAP93.17Unverified
2LSHFM (T: ResNet101 S: MobileNetV2)mAP90.14Unverified
#ModelMetricClaimedVerifiedStatus
1TIE-KD (T: Adabins S: MobileNetV2)RMSE2.43Unverified