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

Showing 21262150 of 10307 papers

TitleStatusHype
GERNERMED++: Transfer Learning in German Medical NLPCode0
GIST at SemEval-2018 Task 12: A network transferring inference knowledge to Argument Reasoning Comprehension taskCode0
Bilingual Alignment Pre-Training for Zero-Shot Cross-Lingual TransferCode0
Geographical Distance Is The New Hyperparameter: A Case Study Of Finding The Optimal Pre-trained Language For English-isiZulu Machine TranslationCode0
Geostatistical Learning: Challenges and OpportunitiesCode0
Generative Transfer Learning: Covid-19 Classification with a few Chest X-ray ImagesCode0
A Deep Learning Method for Comparing Bayesian Hierarchical ModelsCode0
GenSF: Simultaneous Adaptation of Generative Pre-trained Models and Slot FillingCode0
Bilateral Personalized Dialogue Generation with Contrastive LearningCode0
A Neural Grammatical Error Correction System Built On Better Pre-training and Sequential Transfer LearningCode0
GenTL: A General Transfer Learning Model for Building Thermal DynamicsCode0
Generative Denoise Distillation: Simple Stochastic Noises Induce Efficient Knowledge Transfer for Dense PredictionCode0
Generative Causal Representation Learning for Out-of-Distribution Motion ForecastingCode0
Generating Gameplay-Relevant Art Assets with Transfer LearningCode0
Generating Thermal Human Faces for Physiological Assessment Using Thermal Sensor Auxiliary LabelsCode0
Global Safe Sequential Learning via Efficient Knowledge TransferCode0
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related FeaturesCode0
Generalizing over Long Tail Concepts for Medical Term NormalizationCode0
Generalized Funnelling: Ensemble Learning and Heterogeneous Document Embeddings for Cross-Lingual Text ClassificationCode0
Generalizing Teacher Networks for Effective Knowledge Distillation Across Student ArchitecturesCode0
Generalization Through The Lens Of Leave-One-Out ErrorCode0
Generalizable Local Feature Pre-training for Deformable Shape AnalysisCode0
Generalized Adaptive Transfer Network: Enhancing Transfer Learning in Reinforcement Learning Across DomainsCode0
Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative TransferCode0
General-Purpose Deep Point Cloud Feature ExtractorCode0
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Benchmark Results

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