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 1801–1850 of 4240 papers

TitleStatusHype
Intermediate Distillation: Data-Efficient Distillation from Black-Box LLMs for Information Retrieval—0
STEVE Series: Step-by-Step Construction of Agent Systems in Minecraft—0
Mutual Learning for Finetuning Click-Through Rate Prediction Models—0
Graph Knowledge Distillation to Mixture of ExpertsCode0
NLDF: Neural Light Dynamic Fields for Efficient 3D Talking Head Generation—0
Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions—0
Self-Knowledge Distillation for Learning Ambiguity—0
PC-LoRA: Low-Rank Adaptation for Progressive Model Compression with Knowledge Distillation—0
Contextual Distillation Model for Diversified Recommendation—0
DistilDoc: Knowledge Distillation for Visually-Rich Document Applications—0
Adaptive Teaching with Shared Classifier for Knowledge DistillationCode0
Guiding Frame-Level CTC Alignments Using Self-knowledge DistillationCode0
GenDistiller: Distilling Pre-trained Language Models based on an Autoregressive Generative Model—0
Unveiling Incomplete Modality Brain Tumor Segmentation: Leveraging Masked Predicted Auto-Encoder and Divergence Learning—0
Low-Complexity Acoustic Scene Classification Using Parallel Attention-Convolution NetworkCode0
Self-Distillation Learning Based on Temporal-Spatial Consistency for Spiking Neural Networks—0
FastAST: Accelerating Audio Spectrogram Transformer via Token Merging and Cross-Model Knowledge DistillationCode0
TernaryLLM: Ternarized Large Language Model—0
Teaching with Uncertainty: Unleashing the Potential of Knowledge Distillation in Object Detection—0
Weighted KL-Divergence for Document Ranking Model Refinement—0
BS-PLCNet 2: Two-stage Band-split Packet Loss Concealment Network with Intra-model Knowledge Distillation—0
Online Policy Distillation with Decision-Attention—0
Teaching-Assistant-in-the-Loop: Improving Knowledge Distillation from Imperfect Teacher Models in Low-Budget Scenarios—0
Data-Free Generative Replay for Class-Incremental Learning on Imbalanced DataCode0
IOR: Inversed Objects Replay for Incremental Object Detection—0
To Distill or Not to Distill? On the Robustness of Robust Knowledge DistillationCode0
Step Out and Seek Around: On Warm-Start Training with Incremental Data—0
Mutual Information Guided Backdoor Mitigation for Pre-trained Encoders—0
Decision Boundary-aware Knowledge Consolidation Generates Better Instance-Incremental Learner—0
Tiny models from tiny data: Textual and null-text inversion for few-shot distillationCode0
Adversarial Moment-Matching Distillation of Large Language ModelsCode0
PLaD: Preference-based Large Language Model Distillation with Pseudo-Preference Pairs—0
RKLD: Reverse KL-Divergence-based Knowledge Distillation for Unlearning Personal Information in Large Language Models—0
Optimal Transport Guided Correlation Assignment for Multimodal Entity LinkingCode0
DL-KDD: Dual-Light Knowledge Distillation for Action Recognition in the Dark—0
Decoupled Alignment for Robust Plug-and-Play Adaptation—0
Toward Efficient Deep Spiking Neuron Networks:A Survey On Compression—0
Learning Background Prompts to Discover Implicit Knowledge for Open Vocabulary Object Detection—0
Robust Knowledge Distillation Based on Feature Variance Against Backdoored Teacher ModelCode0
Vision-Language Meets the Skeleton: Progressively Distillation with Cross-Modal Knowledge for 3D Action Representation LearningCode0
Adv-KD: Adversarial Knowledge Distillation for Faster Diffusion SamplingCode0
Multi-label Class Incremental Emotion Decoding with Augmented Emotional Semantics Learning—0
WebUOT-1M: Advancing Deep Underwater Object Tracking with A Million-Scale Benchmark—0
GKT: A Novel Guidance-Based Knowledge Transfer Framework For Efficient Cloud-edge Collaboration LLM DeploymentCode0
Estimating Human Poses Across Datasets: A Unified Skeleton and Multi-Teacher Distillation Approach—0
Relation Modeling and Distillation for Learning with Noisy Labels—0
Distribution Aligned Semantics Adaption for Lifelong Person Re-IdentificationCode0
Scalable Detection of Salient Entities in News Articles—0
BLSP-KD: Bootstrapping Language-Speech Pre-training via Knowledge Distillation—0
Forward-Backward Knowledge Distillation for Continual Clustering—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