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 851–900 of 10307 papers

TitleStatusHype
SQ-Whisper: Speaker-Querying based Whisper Model for Target-Speaker ASRCode0
Finite Element Neural Network Interpolation. Part I: Interpretable and Adaptive Discretization for Solving PDEsCode1
Improving data sharing and knowledge transfer via the Neuroelectrophysiology Analysis Ontology (NEAO)—0
Assessing and Learning Alignment of Unimodal Vision and Language Models—0
Expanding Deep Learning-based Sensing Systems with Multi-Source Knowledge Transfer—0
FedMetaMed: Federated Meta-Learning for Personalized Medication in Distributed Healthcare Systems—0
Graph-Sequential Alignment and Uniformity: Toward Enhanced Recommendation SystemsCode0
Representation Purification for End-to-End Speech Translation—0
Adult Glioma Segmentation in Sub-Saharan Africa using Transfer Learning on Stratified Finetuning Data—0
Streaming Detection of Queried Event StartCode0
Hybrid deep learning-based strategy for the hepatocellular carcinoma cancer grade classification of H&E stained liver histopathology images—0
Memory-efficient Continual Learning with Neural Collapse Contrastive—0
Task Adaptation of Reinforcement Learning-based NAS Agents through Transfer Learning—0
A Note on Estimation Error Bound and Grouping Effect of Transfer Elastic Net—0
SiTSE: Sinhala Text Simplification Dataset and EvaluationCode0
IQA-Adapter: Exploring Knowledge Transfer from Image Quality Assessment to Diffusion-based Generative ModelsCode1
The Evolution and Future Perspectives of Artificial Intelligence Generated Content—0
FathomVerse: A community science dataset for ocean animal discovery—0
Command-line Risk Classification using Transformer-based Neural Architectures—0
Transfer Learning for Control Systems via Neural Simulation Relations—0
Patent-publication pairs for the detection of knowledge transfer from research to industry: reducing ambiguities with word embeddings and references—0
Pairwise Discernment of AffectNet Expressions with ArcFace—0
Local vs. Global: Local Land-Use and Land-Cover Models Deliver Higher Quality Maps—0
Pruned Convolutional Attention Network Based Wideband Spectrum Sensing with Sub-Nyquist SamplingCode0
Polish Medical Exams: A new dataset for cross-lingual medical knowledge transfer assessment—0
Transfer Learning for High-dimensional Quantile Regression with Distribution Shift—0
Towards Santali Linguistic Inclusion: Building the First Santali-to-English Translation Model using mT5 Transformer and Data Augmentation—0
LokiTalk: Learning Fine-Grained and Generalizable Correspondences to Enhance NeRF-based Talking Head Synthesis—0
Knowledge Management for Automobile Failure Analysis Using Graph RAG—0
Headache to Overstock? Promoting Long-tail Items through Debiased Product Bundling—0
TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action RecognitionCode1
Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough?—0
Parameter-Efficient Transfer Learning for Music Foundation ModelsCode0
Federated Continual Graph LearningCode0
Pre-Training Graph Contrastive Masked Autoencoders are Strong Distillers for EEG—0
Dual Prototyping with Domain and Class Prototypes for Affective Brain-Computer Interface in Unseen Target Conditions—0
Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits—0
Can bidirectional encoder become the ultimate winner for downstream applications of foundation models?—0
Spectral-Spatial Transformer with Active Transfer Learning for Hyperspectral Image ClassificationCode1
What do physics-informed DeepONets learn? Understanding and improving training for scientific computing applications—0
Using different sources of ground truths and transfer learning to improve the generalization of photometric redshift estimation—0
When does a bridge become an aeroplane?—0
Transfer Learning for Deep Learning-based Prediction of Lattice Thermal ConductivityCode0
Deep learning-based spatio-temporal fusion for high-fidelity ultra-high-speed x-ray radiographyCode0
Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification—0
Breast Tumor Classification Using EfficientNet Deep Learning ModelCode0
Towards Robust Cross-Domain Recommendation with Joint Identifiability of User Preference—0
Learning Hierarchical Polynomials of Multiple Nonlinear Features with Three-Layer Networks—0
Crack Detection in Infrastructure Using Transfer Learning, Spatial Attention, and Genetic Algorithm Optimization—0
On the Generalization of Handwritten Text Recognition Models—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