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 3601–3650 of 4240 papers

TitleStatusHype
High Performance Natural Language Processing—0
Hint-dynamic Knowledge Distillation—0
HIRE: Distilling High-order Relational Knowledge From Heterogeneous Graph Neural Networks—0
HKD4VLM: A Progressive Hybrid Knowledge Distillation Framework for Robust Multimodal Hallucination and Factuality Detection in VLMs—0
Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems—0
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers—0
Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning—0
HoverFast: an accurate, high-throughput, clinically deployable nuclear segmentation tool for brightfield digital pathology images—0
How and When Adversarial Robustness Transfers in Knowledge Distillation?—0
How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation?—0
How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting—0
How Redundant Is the Transformer Stack in Speech Representation Models?—0
How to Backdoor the Knowledge Distillation—0
How to Prune Your Language Model: Recovering Accuracy on the "Sparsity May Cry'' Benchmark—0
How to Select One Among All ? An Empirical Study Towards the Robustness of Knowledge Distillation in Natural Language Understanding—0
HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillation—0
Human-Centered Prior-Guided and Task-Dependent Multi-Task Representation Learning for Action Recognition Pre-Training—0
Human Insights Driven Latent Space for Different Driving Perspectives: A Unified Encoder for Efficient Multi-Task Inference—0
Human in the Latent Loop (HILL): Interactively Guiding Model Training Through Human Intuition—0
Human-Like Active Learning: Machines Simulating the Human Learning Process—0
HW-TSC’s Participation in the WMT 2020 News Translation Shared Task—0
HW-TSC’s Participation in the WMT 2021 Large-Scale Multilingual Translation Task—0
HW-TSC’s Participation in the WMT 2021 News Translation Shared Task—0
Hybrid Paradigm-based Brain-Computer Interface for Robotic Arm Control—0
HYDRA-FL: Hybrid Knowledge Distillation for Robust and Accurate Federated Learning—0
HyperINR: A Fast and Predictive Hypernetwork for Implicit Neural Representations via Knowledge Distillation—0
Hyperspectral Image Analysis in Single-Modal and Multimodal setting using Deep Learning Techniques—0
I2CKD : Intra- and Inter-Class Knowledge Distillation for Semantic Segmentation—0
I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation—0
I^2KD-SLU: An Intra-Inter Knowledge Distillation Framework for Zero-Shot Cross-Lingual Spoken Language Understanding—0
IAG: Induction-Augmented Generation Framework for Answering Reasoning Questions—0
ICD-Face: Intra-class Compactness Distillation for Face Recognition—0
Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation—0
If At First You Don't Succeed: Test Time Re-ranking for Zero-shot, Cross-domain Retrieval—0
IIE’s Neural Machine Translation Systems for WMT20—0
IKD+: Reliable Low Complexity Deep Models For Retinopathy Classification—0
IL-NeRF: Incremental Learning for Neural Radiance Fields with Camera Pose Alignment—0
Image Restoration using Feature-guidance—0
Image-to-Video Re-Identification via Mutual Discriminative Knowledge Transfer—0
Attention-based Knowledge Distillation in Multi-attention Tasks: The Impact of a DCT-driven Loss—0
Implicit Word Reordering with Knowledge Distillation for Cross-Lingual Dependency Parsing—0
Impossible Triangle: What's Next for Pre-trained Language Models?—0
Improved Cross-Lingual Transfer Learning For Automatic Speech Translation—0
Improved Customer Transaction Classification using Semi-Supervised Knowledge Distillation—0
Improved implicit diffusion model with knowledge distillation to estimate the spatial distribution density of carbon stock in remote sensing imagery—0
Improved knowledge distillation by utilizing backward pass knowledge in neural networks—0
Improved Knowledge Distillation for Pre-trained Language Models via Knowledge Selection—0
Improved Knowledge Distillation via Adversarial Collaboration—0
Improved Methods for Model Pruning and Knowledge Distillation—0
Improved Synthetic Training for Reading Comprehension—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