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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 1051–1100 of 4240 papers

TitleStatusHype
Why Knowledge Distillation Works in Generative Models: A Minimal Working Explanation—0
SSR: Enhancing Depth Perception in Vision-Language Models via Rationale-Guided Spatial Reasoning—0
LAMeTA: Intent-Aware Agentic Network Optimization via a Large AI Model-Empowered Two-Stage Approach—0
Denoising Mutual Knowledge Distillation in Bi-Directional Multiple Instance Learning—0
On Membership Inference Attacks in Knowledge DistillationCode0
FiGKD: Fine-Grained Knowledge Distillation via High-Frequency Detail Transfer—0
Bidirectional Distillation: A Mixed-Play Framework for Multi-Agent Generalizable Behaviors—0
Distilled Circuits: A Mechanistic Study of Internal Restructuring in Knowledge DistillationCode0
Semantically-Aware Game Image Quality Assessment—0
Advancing Multiple Instance Learning with Continual Learning for Whole Slide Imaging—0
DCSNet: A Lightweight Knowledge Distillation-Based Model with Explainable AI for Lung Cancer Diagnosis from Histopathological Images—0
Low-Complexity Inference in Continual Learning via Compressed Knowledge Transfer—0
MoKD: Multi-Task Optimization for Knowledge Distillation—0
Fusing Bidirectional Chains of Thought and Reward Mechanisms A Method for Enhancing Question-Answering Capabilities of Large Language Models for Chinese Intangible Cultural Heritage—0
Simple Semi-supervised Knowledge Distillation from Vision-Language Models via Dual-Head OptimizationCode0
Ranking-aware Continual Learning for LiDAR Place Recognition—0
Channel Fingerprint Construction for Massive MIMO: A Deep Conditional Generative Approach—0
Topology-Guided Knowledge Distillation for Efficient Point Cloud ProcessingCode0
KDH-MLTC: Knowledge Distillation for Healthcare Multi-Label Text Classification—0
An Extra RMSNorm is All You Need for Fine Tuning to 1.58 Bits—0
Knowledge Distillation for Enhancing Walmart E-commerce Search Relevance Using Large Language Models—0
Human in the Latent Loop (HILL): Interactively Guiding Model Training Through Human Intuition—0
Robust & Precise Knowledge Distillation-based Novel Context-Aware Predictor for Disease Detection in Brain and Gastrointestinal—0
Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization—0
Biomed-DPT: Dual Modality Prompt Tuning for Biomedical Vision-Language ModelsCode0
Theoretical Guarantees for LT-TTD: A Unified Transformer-based Architecture for Two-Level Ranking Systems—0
Image Recognition with Online Lightweight Vision Transformer: A SurveyCode0
Knowledge Distillation for Speech Denoising by Latent Representation Alignment with Cosine Distance—0
SepALM: Audio Language Models Are Error Correctors for Robust Speech Separation—0
Action Spotting and Precise Event Detection in Sports: Datasets, Methods, and Challenges—0
Artificial Behavior Intelligence: Technology, Challenges, and Future Directions—0
End-to-end fully-binarized network design: from Generic Learned Thermometer to Block Pruning—0
AKD : Adversarial Knowledge Distillation For Large Language Models Alignment on Coding tasks—0
FedSDAF: Leveraging Source Domain Awareness for Enhanced Federated Domain GeneralizationCode0
Optimizing LLMs for Resource-Constrained Environments: A Survey of Model Compression Techniques—0
Segment Any RGB-Thermal Model with Language-aided Distillation—0
High-Fidelity Pseudo-label Generation by Large Language Models for Training Robust Radiology Report Classifiers—0
Toward Data-centric Directed Graph Learning: An Entropy-driven Approach—0
Llama-Nemotron: Efficient Reasoning Models—0
Uncertainty-Aware Multi-Expert Knowledge Distillation for Imbalanced Disease Grading—0
Enhancing New-item Fairness in Dynamic Recommender SystemsCode0
CAE-DFKD: Bridging the Transferability Gap in Data-Free Knowledge Distillation—0
How to Backdoor the Knowledge Distillation—0
The Estimation of Continual Causal Effect for Dataset Shifting Streams—0
Head-Tail-Aware KL Divergence in Knowledge Distillation for Spiking Neural Networks—0
DS_FusionNet: Dynamic Dual-Stream Fusion with Bidirectional Knowledge Distillation for Plant Disease RecognitionCode0
Trace-of-Thought Prompting: Investigating Prompt-Based Knowledge Distillation Through Question Decomposition—0
SAM-Guided Robust Representation Learning for One-Shot 3D Medical Image Segmentation—0
Federated One-Shot Learning with Data Privacy and Objective-Hiding—0
Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom—0
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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