SOTAVerified

Transfer Learning

Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.

( Image credit: Subodh Malgonde )

Papers

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Showing 901–950 of 10307 papers

TitleStatusHype
ParsTwiNER: A Corpus for Named Entity Recognition at Informal PersianCode1
FinEAS: Financial Embedding Analysis of SentimentCode1
DOCKSTRING: easy molecular docking yields better benchmarks for ligand designCode1
Mosaicking to Distill: Knowledge Distillation from Out-of-Domain DataCode1
Meta-Knowledge Transfer for Inductive Knowledge Graph EmbeddingCode1
Algorithmic encoding of protected characteristics in image-based models for disease detectionCode1
Modular Gaussian Processes for Transfer LearningCode1
AVocaDo: Strategy for Adapting Vocabulary to Downstream DomainCode1
YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUsCode1
Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment AnalysisCode1
AFEC: Active Forgetting of Negative Transfer in Continual LearningCode1
StyleAlign: Analysis and Applications of Aligned StyleGAN ModelsCode1
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIPCode1
One-Shot Transfer Learning of Physics-Informed Neural NetworksCode1
Few-Shot Temporal Action Localization with Query Adaptive TransformerCode1
Text-Based Person Search with Limited DataCode1
CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel SynthesisCode1
Hydra: A System for Large Multi-Model Deep LearningCode1
Malaria Parasite Detection using Efficient Neural EnsemblesCode1
Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language ModelsCode1
Self-Supervised Learning by Estimating Twin Class DistributionsCode1
A Comprehensive Study on Torchvision Pre-trained Models for Fine-grained Inter-species ClassificationCode1
Composable Sparse Fine-Tuning for Cross-Lingual TransferCode1
Performance Evaluation of Deep Transfer Learning on Multiclass Identification of Common Weed Species in Cotton Production SystemsCode1
Chaos as an interpretable benchmark for forecasting and data-driven modellingCode1
TCube: Domain-Agnostic Neural Time-series NarrationCode1
Vector-quantized Image Modeling with Improved VQGANCode1
Neural Model Reprogramming with Similarity Based Mapping for Low-Resource Spoken Command RecognitionCode1
Towards a Unified View of Parameter-Efficient Transfer LearningCode1
Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot FillingCode1
Study on Transfer Learning Capabilities for Pneumonia Classification in Chest-X-Rays ImageCode1
Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative StudyCode1
KNOT: Knowledge Distillation using Optimal Transport for Solving NLP TasksCode1
PoNet: Pooling Network for Efficient Token Mixing in Long SequencesCode1
Transfer Learning U-Net Deep Learning for Lung Ultrasound SegmentationCode1
Self-Supervised Generative Style Transfer for One-Shot Medical Image SegmentationCode1
MEBeauty: a multi-ethnic facial beauty dataset in-the-wildCode1
Revisiting Self-Training for Few-Shot Learning of Language ModelCode1
Machine Learning with Knowledge Constraints for Process Optimization of Open-Air Perovskite Solar Cell ManufacturingCode1
Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional NetworkCode1
Transfer Learning Based Multi-Objective Genetic Algorithm for Dynamic Community DetectionCode1
HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot LearningCode1
PASS: An ImageNet replacement for self-supervised pretraining without humansCode1
AutoGCL: Automated Graph Contrastive Learning via Learnable View GeneratorsCode1
Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-RefinementCode1
AutoInit: Analytic Signal-Preserving Weight Initialization for Neural NetworksCode1
Seeking an Optimal Approach for Computer-Aided Pulmonary Embolism DetectionCode1
Does Pretraining for Summarization Require Knowledge Transfer?Code1
Zero-Shot Dialogue State Tracking via Cross-Task TransferCode1
Choquet Integral and Coalition Game-based Ensemble of Deep Learning Models for COVID-19 Screening from Chest X-ray ImagesCode1
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All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified