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 3201–3250 of 10307 papers

TitleStatusHype
Distilling Efficient Language-Specific Models for Cross-Lingual TransferCode0
DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model—0
On the Robustness of Arabic Speech Dialect Identification—0
TMI! Finetuned Models Leak Private Information from their Pretraining DataCode0
Improving Polish to English Neural Machine Translation with Transfer Learning: Effects of Data Volume and Language Similarity—0
Improved Cross-Lingual Transfer Learning For Automatic Speech Translation—0
The Effects of Input Type and Pronunciation Dictionary Usage in Transfer Learning for Low-Resource Text-to-Speech—0
Divide, Conquer, and Combine: Mixture of Semantic-Independent Experts for Zero-Shot Dialogue State Tracking—0
Maximal Domain Independent Representations Improve Transfer Learning—0
Autism Disease Detection Using Transfer Learning Techniques: Performance Comparison Between Central Processing Unit vs Graphics Processing Unit Functions for Neural Networks—0
Adapting Pre-trained Language Models to Vision-Language Tasks via Dynamic Visual PromptingCode0
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior—0
Transfer Learning for Underrepresented Music Generation—0
CL-MRI: Self-Supervised Contrastive Learning to Improve the Accuracy of Undersampled MRI ReconstructionCode0
Fish-TViT: A novel fish species classification method in multi water areas based on transfer learning and vision transformer—0
CrystalGPT: Enhancing system-to-system transferability in crystallization prediction and control using time-series-transformers—0
Adaptive ship-radiated noise recognition with learnable fine-grained wavelet transform—0
Simple yet Effective Code-Switching Language Identification with Multitask Pre-Training and Transfer Learning—0
SLABERT Talk Pretty One Day: Modeling Second Language Acquisition with BERT—0
Additional Positive Enables Better Representation Learning for Medical Images—0
Pre-Trained Language-Meaning Models for Multilingual Parsing and GenerationCode0
MetaXLR -- Mixed Language Meta Representation Transformation for Low-resource Cross-lingual Learning based on Multi-Armed BanditCode0
VIPriors 3: Visual Inductive Priors for Data-Efficient Deep Learning Challenges—0
Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color ContrastCode1
Deep into The Domain Shift: Transfer Learning through Dependence RegularizationCode0
A Survey of Label-Efficient Deep Learning for 3D Point CloudsCode1
Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability—0
Multitask learning for recognizing stress and depression in social media—0
Perturbation-Assisted Sample Synthesis: A Novel Approach for Uncertainty QuantificationCode0
Cross Encoding as Augmentation: Towards Effective Educational Text Classification—0
AdapterEM: Pre-trained Language Model Adaptation for Generalized Entity Matching using Adapter-tuningCode0
Multi-source adversarial transfer learning based on similar source domains with local features—0
Calliffusion: Chinese Calligraphy Generation and Style Transfer with Diffusion Modeling—0
Multi-source adversarial transfer learning for ultrasound image segmentation with limited similarity—0
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement LearningCode1
A Transfer Learning and Explainable Solution to Detect mpox from Smartphones imagesCode0
Deeply Coupled Cross-Modal Prompt LearningCode1
JutePestDetect: An Intelligent Approach for Jute Pest Identification Using Fine-Tuned Transfer Learning—0
Transfer Learning for Power Outage Detection Task with Limited Training Data—0
Augmenting Character Designers Creativity Using Generative Adversarial Networks—0
One Network, Many Masks: Towards More Parameter-Efficient Transfer LearningCode1
PotatoPestNet: A CTInceptionV3-RS-Based Neural Network for Accurate Identification of Potato Pests—0
Enhancing Translation for Indigenous Languages: Experiments with Multilingual Models—0
FoPro-KD: Fourier Prompted Effective Knowledge Distillation for Long-Tailed Medical Image RecognitionCode1
Parallel Corpus for Indigenous Language Translation: Spanish-Mazatec and Spanish-MixtecCode0
A Comprehensive Overview and Comparative Analysis on Deep Learning Models: CNN, RNN, LSTM, GRU—0
Matrix Information Theory for Self-Supervised LearningCode1
Vision Transformers for Small Histological Datasets Learned through Knowledge DistillationCode0
GVdoc: Graph-based Visual Document ClassificationCode0
Double Descent and Overfitting under Noisy Inputs and Distribution Shift for Linear Denoisers—0
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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