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 20262050 of 10307 papers

TitleStatusHype
MisRoBÆRTa: Transformers versus MisinformationCode0
Graph Few-shot Learning via Knowledge TransferCode0
Breast Tumor Classification Using EfficientNet Deep Learning ModelCode0
Breast-NET: a lightweight DCNN model for breast cancer detection and grading using histological samplesCode0
GPT-3 Models are Poor Few-Shot Learners in the Biomedical DomainCode0
Gotta Learn Fast: A New Benchmark for Generalization in RLCode0
Breast Mass Classification from Mammograms using Deep Convolutional Neural NetworksCode0
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot TranslationCode0
Breast cancer histology classification using Deep Residual NetworksCode0
Google Vizier: A Service for Black-Box OptimizationCode0
Grad2Task: Improved Few-shot Text Classification Using Gradients for Task RepresentationCode0
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable RepresentationsCode0
AdPE: Adversarial Positional Embeddings for Pretraining Vision Transformers via MAE+Code0
An Information-Theoretic Metric of Transferability for Task Transfer LearningCode0
Global Safe Sequential Learning via Efficient Knowledge TransferCode0
Brain Tumor Synthetic Data Generation with Adaptive StyleGANsCode0
A Contrastive Knowledge Transfer Framework for Model Compression and Transfer LearningCode0
Adaptation of Tacotron2-based Text-To-Speech for Articulatory-to-Acoustic Mapping using Ultrasound Tongue ImagingCode0
Glo-In-One-v2: Holistic Identification of Glomerular Cells, Tissues, and Lesions in Human and Mouse HistopathologyCode0
GIST at SemEval-2018 Task 12: A network transferring inference knowledge to Argument Reasoning Comprehension taskCode0
Getting aligned on representational alignmentCode0
Brain MRI Image Super Resolution using Phase Stretch Transform and Transfer LearningCode0
GERNERMED++: Transfer Learning in German Medical NLPCode0
GKT: A Novel Guidance-Based Knowledge Transfer Framework For Efficient Cloud-edge Collaboration LLM DeploymentCode0
An Information-Geometric Distance on the Space of TasksCode0
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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