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 18511875 of 4240 papers

TitleStatusHype
Adaptive Multi-Teacher Knowledge Distillation with Meta-LearningCode1
GKD: A General Knowledge Distillation Framework for Large-scale Pre-trained Language ModelCode1
EaSyGuide : ESG Issue Identification Framework leveraging Abilities of Generative Large Language ModelsCode0
Are Intermediate Layers and Labels Really Necessary? A General Language Model Distillation MethodCode1
Improving Frame-level Classifier for Word Timings with Non-peaky CTC in End-to-End Automatic Speech Recognition0
RankFormer: Listwise Learning-to-Rank Using Listwide LabelsCode1
The economic trade-offs of large language models: A case study0
BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping0
Population-Based Evolutionary Gaming for Unsupervised Person Re-identification0
Faithful Knowledge Distillation0
Self-supervised Audio Teacher-Student Transformer for Both Clip-level and Frame-level TasksCode1
Model-Based Reinforcement Learning with Multi-Task Offline PretrainingCode0
Orca: Progressive Learning from Complex Explanation Traces of GPT-4Code1
Zero shot framework for satellite image restoration0
Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge GraphsCode0
I^3 Retriever: Incorporating Implicit Interaction in Pre-trained Language Models for Passage RetrievalCode1
Modular Transformers: Compressing Transformers into Modularized Layers for Flexible Efficient Inference0
Revisiting Data-Free Knowledge Distillation with Poisoned TeachersCode1
Evolving Knowledge Mining for Class Incremental SegmentationCode0
Deep Classifier Mimicry without Data AccessCode0
Speech Translation with Foundation Models and Optimal Transport: UPC at IWSLT230
Group channel pruning and spatial attention distilling for object detection0
Privacy Distillation: Reducing Re-identification Risk of Multimodal Diffusion Models0
Teacher Agent: A Knowledge Distillation-Free Framework for Rehearsal-based Video Incremental LearningCode0
Improved Cross-Lingual Transfer Learning For Automatic Speech Translation0
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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