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 2951–3000 of 4240 papers

TitleStatusHype
TrustAL: Trustworthy Active Learning using Knowledge Distillation—0
TSAK: Two-Stage Semantic-Aware Knowledge Distillation for Efficient Wearable Modality and Model Optimization in Manufacturing Lines—0
TS-HTFA: Advancing Time Series Forecasting via Hierarchical Text-Free Alignment with Large Language Models—0
TT-MPD: Test Time Model Pruning and Distillation—0
TTT-KD: Test-Time Training for 3D Semantic Segmentation through Knowledge Distillation from Foundation Models—0
Turbo2K: Towards Ultra-Efficient and High-Quality 2K Video Synthesis—0
TutorNet: Towards Flexible Knowledge Distillation for End-to-End Speech Recognition—0
Twin Network Augmentation: A Novel Training Strategy for Improved Spiking Neural Networks and Efficient Weight Quantization—0
Two-in-one Knowledge Distillation for Efficient Facial Forgery Detection—0
Two-Pass End-to-End ASR Model Compression—0
Two-Stage Multi-task Self-Supervised Learning for Medical Image Segmentation—0
Two-Step Knowledge Distillation for Tiny Speech Enhancement—0
UB-FineNet: Urban Building Fine-grained Classification Network for Open-access Satellite Images—0
Multi-trial Neural Architecture Search with Lottery Tickets—0
UIFormer: A Unified Transformer-based Framework for Incremental Few-Shot Object Detection and Instance Segmentation—0
UKD: Debiasing Conversion Rate Estimation via Uncertainty-regularized Knowledge Distillation—0
U-Know-DiffPAN: An Uncertainty-aware Knowledge Distillation Diffusion Framework with Details Enhancement for PAN-Sharpening—0
Ultrafast Video Attention Prediction with Coupled Knowledge Distillation—0
Uncertainty-Aware Cross-Modal Knowledge Distillation with Prototype Learning for Multimodal Brain-Computer Interfaces—0
Uncertainty-Aware Knowledge Distillation for Compact and Efficient 6DoF Pose Estimation—0
Uncertainty-Aware Multi-Expert Knowledge Distillation for Imbalanced Disease Grading—0
Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification—0
Uncertainty-Guided Never-Ending Learning to Drive—0
Understanding Adversarial Attacks on Autoencoders—0
Understanding and Improving Knowledge Distillation—0
Understanding and Improving Lexical Choice in Non-Autoregressive Translation—0
Understanding Knowledge Distillation—0
Understanding Knowledge Distillation in Non-autoregressive Machine Translation—0
Understanding the Effect of Data Augmentation on Knowledge Distillation—0
Understanding the Gains from Repeated Self-Distillation—0
Understanding the Overfitting of the Episodic Meta-training—0
Understanding the Success of Knowledge Distillation -- A Data Augmentation Perspective—0
UNDO: Understanding Distillation as Optimization—0
UniCompress: Enhancing Multi-Data Medical Image Compression with Knowledge Distillation—0
UNIDEAL: Curriculum Knowledge Distillation Federated Learning—0
Unified and Effective Ensemble Knowledge Distillation—0
Unified Anomaly Detection methods on Edge Device using Knowledge Distillation and Quantization—0
Unified Attacks to Large Language Model Watermarks: Spoofing and Scrubbing in Unauthorized Knowledge Distillation—0
Unified Locomotion Transformer with Simultaneous Sim-to-Real Transfer for Quadrupeds—0
UniKD: Universal Knowledge Distillation for Mimicking Homogeneous or Heterogeneous Object Detectors—0
Unimodal-driven Distillation in Multimodal Emotion Recognition with Dynamic Fusion—0
UniMS: A Unified Framework for Multimodal Summarization with Knowledge Distillation—0
Uni-Retriever: Towards Learning The Unified Embedding Based Retriever in Bing Sponsored Search—0
Dual-mode ASR: Unify and Improve Streaming ASR with Full-context Modeling—0
Universal-KD: Attention-based Output-Grounded Intermediate Layer Knowledge Distillation—0
Unlabeled Data Deployment for Classification of Diabetic Retinopathy Images Using Knowledge Transfer—0
Unlearning Clients, Features and Samples in Vertical Federated Learning—0
Unlearning via Sparse Representations—0
Unleashing the Potential of Mamba: Boosting a LiDAR 3D Sparse Detector by Using Cross-Model Knowledge Distillation—0
Unlimited Knowledge Distillation for Action Recognition in the Dark—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