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 1051–1100 of 4240 papers

TitleStatusHype
DεpS: Delayed ε-Shrinking for Faster Once-For-All Training—0
Boosting Graph Neural Networks via Adaptive Knowledge Distillation—0
Deploying a BERT-based Query-Title Relevance Classifier in a Production System: a View from the Trenches—0
Analyzing Knowledge Distillation in Neural Machine Translation—0
Efficient Intent-Based Filtering for Multi-Party Conversations Using Knowledge Distillation from LLMs—0
Densely Distilling Cumulative Knowledge for Continual Learning—0
Boosting Contrastive Learning with Relation Knowledge Distillation—0
BoostingBERT:Integrating Multi-Class Boosting into BERT for NLP Tasks—0
Denoising Mutual Knowledge Distillation in Bi-Directional Multiple Instance Learning—0
Analyzing Compression Techniques for Computer Vision—0
Efficient Image Compression Using Advanced State Space Models—0
Demystifying Catastrophic Forgetting in Two-Stage Incremental Object Detector—0
Delving Deep into Semantic Relation Distillation—0
Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation—0
BOLT: Bootstrap Long Chain-of-Thought in Language Models without Distillation—0
An Active Learning Framework for Inclusive Generation by Large Language Models—0
Adaptive Regularization of Labels—0
Efficient Inference via Universal LSH Kernel—0
Efficient Knowledge Distillation of SAM for Medical Image Segmentation—0
DeGAN : Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier—0
BLSP-KD: Bootstrapping Language-Speech Pre-training via Knowledge Distillation—0
AMTSS: An Adaptive Multi-Teacher Single-Student Knowledge Distillation Framework For Multilingual Language Inference—0
Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training—0
Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training—0
Deep versus Wide: An Analysis of Student Architectures for Task-Agnostic Knowledge Distillation of Self-Supervised Speech Models—0
Deep-to-bottom Weights Decay: A Systemic Knowledge Review Learning Technique for Transformer Layers in Knowledge Distillation—0
Block-wise Intermediate Representation Training for Model Compression—0
Efficient Gravitational Wave Parameter Estimation via Knowledge Distillation: A ResNet1D-IAF Approach—0
Deep Serial Number: Computational Watermarking for DNN Intellectual Property Protection—0
Bidirectional Distillation: A Mixed-Play Framework for Multi-Agent Generalizable Behaviors—0
Deep Semi-Supervised and Self-Supervised Learning for Diabetic Retinopathy Detection—0
Amortized Noisy Channel Neural Machine Translation—0
Efficient Federated Learning for AIoT Applications Using Knowledge Distillation—0
Deep Representation Learning of Patient Data from Electronic Health Records (EHR): A Systematic Review—0
Black-box Source-free Domain Adaptation via Two-stage Knowledge Distillation—0
Deep Neural Network Models Compression—0
Deep Neural Compression Via Concurrent Pruning and Self-Distillation—0
Efficient Evaluation-Time Uncertainty Estimation by Improved Distillation—0
Efficient Hybrid Language Model Compression through Group-Aware SSM Pruning—0
Efficient Knowledge Distillation via Curriculum Extraction—0
Deep Net Triage: Analyzing the Importance of Network Layers via Structural Compression—0
Black-Box Dissector: Towards Erasing-based Hard-Label Model Stealing Attack—0
Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Study—0
Knowledge Distillation-aided End-to-End Learning for Linear Precoding in Multiuser MIMO Downlink Systems with Finite-Rate Feedback—0
Deep Epidemiological Modeling by Black-box Knowledge Distillation: An Accurate Deep Learning Model for COVID-19—0
BJTU-WeChat's Systems for the WMT22 Chat Translation Task—0
AMLN: Adversarial-based Mutual Learning Network for Online Knowledge Distillation—0
Efficient Compression of Multitask Multilingual Speech Models—0
Efficient AI in Practice: Training and Deployment of Efficient LLMs for Industry Applications—0
Deep Collective Knowledge Distillation—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