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

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Showing 51–100 of 4240 papers

TitleStatusHype
Knowledge Distillation in YOLOX-ViT for Side-Scan Sonar Object DetectionCode2
Learning an Adaptive and View-Invariant Vision Transformer for Real-Time UAV TrackingCode2
LightGNN: Simple Graph Neural Network for RecommendationCode2
Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge DistillationCode2
From Instance Training to Instruction Learning: Task Adapters Generation from InstructionsCode2
BiM-VFI: directional Motion Field-Guided Frame Interpolation for Video with Non-uniform MotionsCode2
Incremental Sequence Labeling: A Tale of Two ShiftsCode2
On-Device Domain GeneralizationCode2
A Cognitive-Based Trajectory Prediction Approach for Autonomous DrivingCode2
Optimizing Edge AI: A Comprehensive Survey on Data, Model, and System StrategiesCode2
Pre-trained Vision and Language Transformers Are Few-Shot Incremental LearnersCode2
Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model InferenceCode2
ESP-MedSAM: Efficient Self-Prompting SAM for Universal Domain-Generalized Medical Image SegmentationCode2
Focal Loss for Dense Object DetectionCode2
JL1-CD: A New Benchmark for Remote Sensing Change Detection and a Robust Multi-Teacher Knowledge Distillation FrameworkCode2
Lightweight and High-Fidelity End-to-End Text-to-Speech with Multi-Band Generation and Inverse Short-Time Fourier TransformCode2
Efficient Large-scale Audio Tagging via Transformer-to-CNN Knowledge DistillationCode2
ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt TuningCode2
Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge DistillationCode2
Distillation-Supervised Convolutional Low-Rank Adaptation for Efficient Image Super-ResolutionCode2
Diffusion Time-step Curriculum for One Image to 3D GenerationCode2
A Survey on Open-Vocabulary Detection and Segmentation: Past, Present, and FutureCode2
Distillation-Free One-Step Diffusion for Real-World Image Super-ResolutionCode2
DOT: A Distillation-Oriented TrainerCode2
Dual-Space Knowledge Distillation for Large Language ModelsCode2
Dynamic Convolutional Neural Networks as Efficient Pre-trained Audio ModelsCode2
ConDistFL: Conditional Distillation for Federated Learning from Partially Annotated DataCode2
A Comprehensive Survey on Knowledge DistillationCode2
A Unified Framework for 3D Scene UnderstandingCode2
EPTQ: Enhanced Post-Training Quantization via Hessian-guided Network-wise OptimizationCode2
Event Stream-based Visual Object Tracking: HDETrack V2 and A High-Definition BenchmarkCode2
Event Stream-based Visual Object Tracking: A High-Resolution Benchmark Dataset and A Novel BaselineCode2
Cross-Image Relational Knowledge Distillation for Semantic SegmentationCode2
OBSeg: Accurate and Fast Instance Segmentation Framework Using Segmentation Foundation Models with Oriented Bounding Box PromptsCode2
Improving the Training of Rectified FlowsCode2
Data-Free Knowledge Distillation for Deep Neural NetworksCode2
Knowledge distillation: A good teacher is patient and consistentCode2
Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New OutlooksCode2
MiniLLM: Knowledge Distillation of Large Language ModelsCode2
Large Language Models are Efficient Learners of Noise-Robust Speech RecognitionCode2
Learning Occlusion-Robust Vision Transformers for Real-Time UAV TrackingCode2
Learning Student Networks in the WildCode2
LibFewShot: A Comprehensive Library for Few-shot LearningCode2
LibreFace: An Open-Source Toolkit for Deep Facial Expression AnalysisCode2
Are Large Kernels Better Teachers than Transformers for ConvNets?Code2
LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and DistillationCode2
Positive-Unlabeled Compression on the CloudCode2
2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point CloudsCode2
Masked Generative DistillationCode2
Can LLMs Learn by Teaching for Better Reasoning? A Preliminary StudyCode2
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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