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 32513275 of 4240 papers

TitleStatusHype
Multi-granularity for knowledge distillationCode0
Online Continual Learning For Visual Food Classification0
AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric LearningCode1
PAIR: Leveraging Passage-Centric Similarity Relation for Improving Dense Passage Retrieval0
Learning from Matured Dumb Teacher for Fine Generalization0
Distilling Holistic Knowledge with Graph Neural NetworksCode1
Semi-Supervised Domain Generalizable Person Re-IdentificationCode2
Preventing Catastrophic Forgetting and Distribution Mismatch in Knowledge Distillation via Synthetic Data0
Lifelong Intent Detection via Multi-Strategy Rebalancing0
Learning an Augmented RGB Representation with Cross-Modal Knowledge Distillation for Action Detection0
A distillation based approach for the diagnosis of diseases0
Spatio-Temporal Attention Mechanism and Knowledge Distillation for Lip Reading0
Transferring Knowledge Distillation for Multilingual Social Event DetectionCode1
Decoupled Transformer for Scalable Inference in Open-domain Question Answering0
Knowledge Distillation from BERT Transformer to Speech Transformer for Intent ClassificationCode1
WeChat Neural Machine Translation Systems for WMT210
MS-KD: Multi-Organ Segmentation with Multiple Binary-Labeled Datasets0
Online Knowledge Distillation for Efficient Pose EstimationCode1
Learning Compatible EmbeddingsCode1
Semi-Supervising Learning, Transfer Learning, and Knowledge Distillation with SimCLR0
In-Batch Negatives for Knowledge Distillation with Tightly-Coupled Teachers for Dense Retrieval0
On Knowledge Distillation for Translating Erroneous Speech Transcriptions0
NAIST English-to-Japanese Simultaneous Translation System for IWSLT 2021 Simultaneous Text-to-text Task0
The USYD-JD Speech Translation System for IWSLT20210
基于层间知识蒸馏的神经机器翻译(Inter-layer Knowledge Distillation for Neural Machine Translation)0
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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