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 2851–2900 of 4240 papers

TitleStatusHype
C3R: Channel Conditioned Cell Representations for unified evaluation in microscopy imaging—0
CAE-DFKD: Bridging the Transferability Gap in Data-Free Knowledge Distillation—0
CAKD: A Correlation-Aware Knowledge Distillation Framework Based on Decoupling Kullback-Leibler Divergence—0
CAMeMBERT: Cascading Assistant-Mediated Multilingual BERT—0
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 Fairness—0
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-Thought—0
Can Students Beyond The Teacher? Distilling Knowledge from Teacher's Bias—0
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 Purification—0
CapsuleRRT: Relationships-Aware Regression Tracking via Capsules—0
Capturing Rich Behavior Representations: A Dynamic Action Semantic-Aware Graph Transformer for Video Captioning—0
Cascaded channel pruning using hierarchical self-distillation—0
CASIA's System for IWSLT 2020 Open Domain Translation—0
CAST: Contrastive Adaptation and Distillation for Semi-Supervised Instance Segmentation—0
Categories of Response-Based, Feature-Based, and Relation-Based Knowledge Distillation—0
Causality Enhanced Origin-Destination Flow Prediction in Data-Scarce Cities—0
Causal Self-supervised Pretrained Frontend with Predictive Code for Speech Separation—0
Causes of Catastrophic Forgetting in Class-Incremental Semantic Segmentation—0
CBNN: 3-Party Secure Framework for Customized Binary Neural Networks Inference—0
CCFace: Classification Consistency for Low-Resolution Face Recognition—0
CCS: Continuous Learning for Customized Incremental Wireless Sensing Services—0
CDKT-FL: Cross-Device Knowledge Transfer using Proxy Dataset in Federated Learning—0
CEKD:Cross Ensemble Knowledge Distillation for Augmented Fine-grained Data—0
Centerness-based Instance-aware Knowledge Distillation with Task-wise Mutual Lifting for Object Detection on Drone Imagery—0
CES-KD: Curriculum-based Expert Selection for Guided Knowledge Distillation—0
Order of Compression: A Systematic and Optimal Sequence to Combinationally Compress CNN—0
Channel Fingerprint Construction for Massive MIMO: A Deep Conditional Generative Approach—0
Channel Planting for Deep Neural Networks using Knowledge Distillation—0
Channel Self-Supervision for Online Knowledge Distillation—0
CILDA: Contrastive Data Augmentation using Intermediate Layer Knowledge Distillation—0
Improving Acoustic Scene Classification with City Features—0
CK4Gen: A Knowledge Distillation Framework for Generating High-Utility Synthetic Survival Datasets in Healthcare—0
Claim Matching Beyond English to Scale Global Fact-Checking—0
Class-aware Information for Logit-based Knowledge Distillation—0
CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks—0
Classification of Diabetic Retinopathy Using Unlabeled Data and Knowledge Distillation—0
Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Evolvability—0
Class-Incremental Continual Learning into the eXtended DER-verse—0
Class-Incremental Few-Shot Event Detection—0
Class-Incremental Few-Shot Object Detection—0
Class-Incremental Learning for Action Recognition in Videos—0
Class-Incremental Learning of Plant and Disease Detection: Growing Branches with Knowledge Distillation—0
Class Incremental Learning with Self-Supervised Pre-Training and Prototype Learning—0
Class Incremental Online Streaming Learning—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