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 28512875 of 4240 papers

TitleStatusHype
C3R: Channel Conditioned Cell Representations for unified evaluation in microscopy imaging0
CAE-DFKD: Bridging the Transferability Gap in Data-Free Knowledge Distillation0
CAKD: A Correlation-Aware Knowledge Distillation Framework Based on Decoupling Kullback-Leibler Divergence0
CAMeMBERT: Cascading Assistant-Mediated Multilingual BERT0
Can a student Large Language Model perform as well as it's teacher?0
Can Current Explainability Help Provide References in Clinical Notes to Support Humans Annotate Medical Codes?0
Can LLMs Revolutionize the Design of Explainable and Efficient TinyML Models?0
Can Low-Rank Knowledge Distillation in LLMs be Useful for Microelectronic Reasoning?0
Can Model Compression Improve NLP Fairness0
Can Small Language Models be Good Reasoners for Sequential Recommendation?0
Can Small Language Models Help Large Language Models Reason Better?: LM-Guided Chain-of-Thought0
Can Students Beyond The Teacher? Distilling Knowledge from Teacher's Bias0
Can Students Outperform Teachers in Knowledge Distillation based Model Compression?0
Can We Use Probing to Better Understand Fine-tuning and Knowledge Distillation of the BERT NLU?0
CAP-GAN: Towards Adversarial Robustness with Cycle-consistent Attentional Purification0
CapsuleRRT: Relationships-Aware Regression Tracking via Capsules0
Capturing Rich Behavior Representations: A Dynamic Action Semantic-Aware Graph Transformer for Video Captioning0
Cascaded channel pruning using hierarchical self-distillation0
CASIA's System for IWSLT 2020 Open Domain Translation0
CAST: Contrastive Adaptation and Distillation for Semi-Supervised Instance Segmentation0
Categories of Response-Based, Feature-Based, and Relation-Based Knowledge Distillation0
Causality Enhanced Origin-Destination Flow Prediction in Data-Scarce Cities0
Causal Self-supervised Pretrained Frontend with Predictive Code for Speech Separation0
Causes of Catastrophic Forgetting in Class-Incremental Semantic Segmentation0
CBNN: 3-Party Secure Framework for Customized Binary Neural Networks Inference0
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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