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 551575 of 4240 papers

TitleStatusHype
Federated Incremental Named Entity RecognitionCode0
Map-Free Trajectory Prediction with Map Distillation and Hierarchical Encoding0
Exploring Feature-based Knowledge Distillation for Recommender System: A Frequency PerspectiveCode0
Multi-perspective Contrastive Logit Distillation0
Hybrid Attention Model Using Feature Decomposition and Knowledge Distillation for Glucose ForecastingCode0
Evidential Federated Learning for Skin Lesion Image Classification0
Mono2Stereo: Monocular Knowledge Transfer for Enhanced Stereo Matching0
VPBSD:Vessel-Pattern-Based Semi-Supervised Distillation for Efficient 3D Microscopic Cerebrovascular Segmentation0
Dual-Head Knowledge Distillation: Enhancing Logits Utilization with an Auxiliary Head0
Federated Graph Learning with Graphless Clients0
UIFormer: A Unified Transformer-based Framework for Incremental Few-Shot Object Detection and Instance Segmentation0
Joint Diffusion models in Continual Learning0
Query Optimization for Parametric Knowledge Refinement in Retrieval-Augmented Large Language Models0
Feature Interaction Fusion Self-Distillation Network For CTR Prediction0
Learning with Less: Knowledge Distillation from Large Language Models via Unlabeled Data0
Quantifying Knowledge Distillation Using Partial Information Decomposition0
LLM-Neo: Parameter Efficient Knowledge Distillation for Large Language ModelsCode1
An Efficient Memory Module for Graph Few-Shot Class-Incremental LearningCode0
ScaleKD: Strong Vision Transformers Could Be Excellent TeachersCode2
SAMPart3D: Segment Any Part in 3D ObjectsCode4
CULL-MT: Compression Using Language and Layer pruning for Machine Translation0
Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge DistillationCode0
Dynamic Textual Prompt For Rehearsal-free Lifelong Person Re-identification0
Multi-Document Financial Question Answering using LLMs0
Mitigating Hallucination with ZeroG: An Advanced Knowledge Management Engine0
Show:102550
← PrevPage 23 of 170Next →

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