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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3251–3300 of 4240 papers

TitleStatusHype
Enhancing Metaphor Detection through Soft Labels and Target Word Prediction—0
Measuring and Reducing Model Update Regression in Structured Prediction for NLP—0
Medical Image Segmentation on MRI Images with Missing Modalities: A Review—0
MEDIC: Remove Model Backdoors via Importance Driven Cloning—0
MedMAP: Promoting Incomplete Multi-modal Brain Tumor Segmentation with Alignment—0
MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models—0
Membership Privacy Protection for Image Translation Models via Adversarial Knowledge Distillation—0
MentalMAC: Enhancing Large Language Models for Detecting Mental Manipulation via Multi-Task Anti-Curriculum Distillation—0
MergeDistill: Merging Pre-trained Language Models using Distillation—0
MergeNet: Knowledge Migration across Heterogeneous Models, Tasks, and Modalities—0
MetaDistiller: Network Self-Boosting via Meta-Learned Top-Down Distillation—0
Meta-Ensemble Parameter Learning—0
Meta-KD: A Meta Knowledge Distillation Framework for Language Model Compression across Domains—0
Meta Knowledge Distillation—0
Meta-Learning across Meta-Tasks for Few-Shot Learning—0
MetaMixer: A Regularization Strategy for Online Knowledge Distillation—0
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis—0
MIAShield: Defending Membership Inference Attacks via Preemptive Exclusion of Members—0
MICIK: MIning Cross-Layer Inherent Similarity Knowledge for Deep Model Compression—0
Microdosing: Knowledge Distillation for GAN based Compression—0
Microsoft Research Asia's Systems for WMT19—0
MIKO: Multimodal Intention Knowledge Distillation from Large Language Models for Social-Media Commonsense Discovery—0
Mimic and Conquer: Heterogeneous Tree Structure Distillation for Syntactic NLP—0
MIND: Modality-Informed Knowledge Distillation Framework for Multimodal Clinical Prediction Tasks—0
Mind the Gap Between Synthetic and Real: Utilizing Transfer Learning to Probe the Boundaries of Stable Diffusion Generated Data—0
Mind the Gap: Promoting Missing Modality Brain Tumor Segmentation with Alignment—0
Minimally Invasive Surgery for Sparse Neural Networks in Contrastive Manner—0
Mini-ResEmoteNet: Leveraging Knowledge Distillation for Human-Centered Design—0
MiniVLN: Efficient Vision-and-Language Navigation by Progressive Knowledge Distillation—0
MinT: Boosting Generalization in Mathematical Reasoning via Multi-View Fine-Tuning—0
Mitigating Cross-client GANs-based Attack in Federated Learning—0
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal—0
Mitigating Hallucination with ZeroG: An Advanced Knowledge Management Engine—0
Mixed Distillation Helps Smaller Language Model Better Reasoning—0
Mixed-Type Wafer Classification For Low Memory Devices Using Knowledge Distillation—0
MixKD: Towards Efficient Distillation of Large-scale Language Models—0
A Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches—0
MKF-ADS: Multi-Knowledge Fusion Based Self-supervised Anomaly Detection System for Control Area Network—0
MK-SGN: A Spiking Graph Convolutional Network with Multimodal Fusion and Knowledge Distillation for Skeleton-based Action Recognition—0
MLKD-BERT: Multi-level Knowledge Distillation for Pre-trained Language Models—0
Multimodal Matching-aware Co-attention Networks with Mutual Knowledge Distillation for Fake News Detection—0
MOBA: Multi-teacher Model Based Reinforcement Learning—0
MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillation—0
Modality-Inconsistent Continual Learning of Multimodal Large Language Models—0
ModalityMirror: Improving Audio Classification in Modality Heterogeneity Federated Learning with Multimodal Distillation—0
MSD: Saliency-aware Knowledge Distillation for Multimodal Understanding—0
Modality-specific Distillation—0
Model-Agnostic Decentralized Collaborative Learning for On-Device POI Recommendation—0
Model Compression and Efficient Inference for Large Language Models: A Survey—0
Model compression for faster structural separation of macromolecules captured by Cellular Electron Cryo-Tomography—0
Show:102550
← PrevPage 66 of 85Next →
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