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 901950 of 4240 papers

TitleStatusHype
BiLD: Bi-directional Logits Difference Loss for Large Language Model DistillationCode1
Inter-Region Affinity Distillation for Road Marking SegmentationCode1
Dice Semimetric Losses: Optimizing the Dice Score with Soft LabelsCode1
Intra-Document Cascading: Learning to Select Passages for Neural Document RankingCode1
DGEKT: A Dual Graph Ensemble Learning Method for Knowledge TracingCode1
Decoupled Multimodal Distilling for Emotion RecognitionCode1
Discriminative and Consistent Representation DistillationCode1
Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose EstimationCode1
DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery CluesCode1
Directed Acyclic Transformer for Non-Autoregressive Machine TranslationCode1
Jaccard Metric Losses: Optimizing the Jaccard Index with Soft LabelsCode1
DeepAqua: Self-Supervised Semantic Segmentation of Wetland Surface Water Extent with SAR Images using Knowledge DistillationCode1
Hybrid Inverted Index Is a Robust Accelerator for Dense RetrievalCode1
TinyGAN: Distilling BigGAN for Conditional Image GenerationCode1
Densely Guided Knowledge Distillation using Multiple Teacher AssistantsCode1
DE-RRD: A Knowledge Distillation Framework for Recommender SystemCode1
Distilling Out-of-Distribution Robustness from Vision-Language Foundation ModelsCode1
Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine TranslationCode1
AMFD: Distillation via Adaptive Multimodal Fusion for Multispectral Pedestrian DetectionCode1
Join the High Accuracy Club on ImageNet with A Binary Neural Network TicketCode1
Deep Graph-level Anomaly Detection by Glocal Knowledge DistillationCode1
DeepKD: A Deeply Decoupled and Denoised Knowledge Distillation TrainerCode1
Learning Cross-Lingual IR from an English RetrieverCode1
KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge DistillationCode1
Adaptive Multi-Teacher Knowledge Distillation with Meta-LearningCode1
KDAS: Knowledge Distillation via Attention Supervision Framework for Polyp SegmentationCode1
Black-box Few-shot Knowledge DistillationCode1
KD-MRI: A knowledge distillation framework for image reconstruction and image restoration in MRI workflowCode1
Adaptive Multi-Teacher Multi-level Knowledge DistillationCode1
KD-MVS: Knowledge Distillation Based Self-supervised Learning for Multi-view StereoCode1
Knapsack Pruning with Inner DistillationCode1
Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance SegmentationCode1
Towards Efficient 3D Object Detection with Knowledge DistillationCode1
Deep Structured Instance Graph for Distilling Object DetectorsCode1
Understanding the Role of the Projector in Knowledge DistillationCode1
Knowledge Condensation DistillationCode1
Learning to Retrieve In-Context Examples for Large Language ModelsCode1
LTE4G: Long-Tail Experts for Graph Neural NetworksCode1
Defocus Blur Detection via Depth DistillationCode1
Deformation Flow Based Two-Stream Network for Lip ReadingCode1
Knowledge Distillation as Efficient Pre-training: Faster Convergence, Higher Data-efficiency, and Better TransferabilityCode1
Deliberated Domain Bridging for Domain Adaptive Semantic SegmentationCode1
Deliberation on Priors: Trustworthy Reasoning of Large Language Models on Knowledge GraphsCode1
Knowledge Distillation for BERT Unsupervised Domain AdaptationCode1
Knowledge Distillation Based on Transformed Teacher MatchingCode1
Traffic Signal Control Using Lightweight Transformers: An Offline-to-Online RL ApproachCode1
Knowledge Distillation for Brain Tumor SegmentationCode1
Knowledge Distillation for Feature Extraction in Underwater VSLAMCode1
Dense Interspecies Face EmbeddingCode1
Multi-Granularity Distillation Scheme Towards Lightweight Semi-Supervised Semantic SegmentationCode1
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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