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 601650 of 4240 papers

TitleStatusHype
Tracking-by-Trackers with a Distilled and Reinforced ModelCode1
Class-incremental Novel Class DiscoveryCode1
Class-relation Knowledge Distillation for Novel Class DiscoveryCode1
Decoupled Multimodal Distilling for Emotion RecognitionCode1
DeepAqua: Self-Supervised Semantic Segmentation of Wetland Surface Water Extent with SAR Images using Knowledge DistillationCode1
I^3 Retriever: Incorporating Implicit Interaction in Pre-trained Language Models for Passage RetrievalCode1
Action knowledge for video captioning with graph neural networksCode1
Deep Graph-level Anomaly Detection by Glocal Knowledge DistillationCode1
Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance SegmentationCode1
Deep Structured Instance Graph for Distilling Object DetectorsCode1
A semi-supervised Teacher-Student framework for surgical tool detection and localizationCode1
Defocus Blur Detection via Depth DistillationCode1
CLIP-Embed-KD: Computationally Efficient Knowledge Distillation Using Embeddings as TeachersCode1
CLIP-guided Federated Learning on Heterogeneous and Long-Tailed DataCode1
CLIP-KD: An Empirical Study of CLIP Model DistillationCode1
CLIP model is an Efficient Continual LearnerCode1
Deliberation on Priors: Trustworthy Reasoning of Large Language Models on Knowledge GraphsCode1
CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental LearningCode1
Dense Interspecies Face EmbeddingCode1
FocusNet: Classifying Better by Focusing on Confusing ClassesCode1
DE-RRD: A Knowledge Distillation Framework for Recommender SystemCode1
Densely Guided Knowledge Distillation using Multiple Teacher AssistantsCode1
Continual Collaborative Distillation for Recommender SystemCode1
Cloud Object Detector Adaptation by Integrating Different Source KnowledgeCode1
Dialogue Chain-of-Thought Distillation for Commonsense-aware Conversational AgentsCode1
CLRKDNet: Speeding up Lane Detection with Knowledge DistillationCode1
Few-Shot Class-Incremental Learning via Class-Aware Bilateral DistillationCode1
Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual LearningCode1
Content-Aware GAN CompressionCode1
CMDFusion: Bidirectional Fusion Network with Cross-modality Knowledge Distillation for LIDAR Semantic SegmentationCode1
CMD: Self-supervised 3D Action Representation Learning with Cross-modal Mutual DistillationCode1
Designing Large Foundation Models for Efficient Training and Inference: A SurveyCode1
Digging into contrastive learning for robust depth estimation with diffusion modelsCode1
Model LEGO: Creating Models Like Disassembling and Assembling Building BlocksCode1
Coaching a Teachable StudentCode1
Extending global-local view alignment for self-supervised learning with remote sensing imageryCode1
FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated LearningCode1
Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge DistillationCode1
ConStyle v2: A Strong Prompter for All-in-One Image RestorationCode1
Consistent Representation Learning for Continual Relation ExtractionCode1
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighterCode1
Distillation from Heterogeneous Models for Top-K RecommendationCode1
Content-Variant Reference Image Quality Assessment via Knowledge DistillationCode1
Distilling Knowledge from Graph Convolutional NetworksCode1
Distillation and Refinement of Reasoning in Small Language Models for Document Re-rankingCode1
Distillation-Based Training for Multi-Exit ArchitecturesCode1
FedUKD: Federated UNet Model with Knowledge Distillation for Land Use Classification from Satellite and Street ViewsCode1
DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge DistillationCode1
Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language ModelCode1
Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated LearningCode1
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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