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
GenFighter: A Generative and Evolutive Textual Attack Removal—0
Neuron Specialization: Leveraging intrinsic task modularity for multilingual machine translation—0
Control Theoretic Approach to Fine-Tuning and Transfer Learning—0
Feature Corrective Transfer Learning: End-to-End Solutions to Object Detection in Non-Ideal Visual Conditions—0
Tao: Re-Thinking DL-based Microarchitecture Simulation—0
Lighter, Better, Faster Multi-Source Domain Adaptation with Gaussian Mixture Models and Optimal TransportCode0
Privacy-Enhanced Training-as-a-Service for On-Device Intelligence: Concept, Architectural Scheme, and Open Problems—0
Conditional Prototype Rectification Prompt LearningCode0
Self-Supervised Learning Featuring Small-Scale Image Dataset for Treatable Retinal Diseases Classification—0
High-Resolution Detection of Earth Structural Heterogeneities from Seismic Amplitudes using Convolutional Neural Networks with Attention layers—0
CREST: Cross-modal Resonance through Evidential Deep Learning for Enhanced Zero-Shot LearningCode0
Intelligent Chemical Purification Technique Based on Machine Learning—0
Breast Cancer Image Classification Method Based on Deep Transfer Learning—0
Evaluating Fast Adaptability of Neural Networks for Brain-Computer InterfaceCode0
Low-Resource Named Entity Recognition with Cross-Lingual, Character-Level Neural Conditional Random Fields—0
FedDistill: Global Model Distillation for Local Model De-Biasing in Non-IID Federated Learning—0
Rethinking Low-Rank Adaptation in Vision: Exploring Head-Level Responsiveness across Diverse Tasks—0
Investigating Neural Machine Translation for Low-Resource Languages: Using Bavarian as a Case StudyCode0
Transfer Learning Study of Motion Transformer-based Trajectory Predictions—0
Advanced wood species identification based on multiple anatomical sections and using deep feature transfer and fusion—0
Using Explainable AI and Transfer Learning to understand and predict the maintenance of Atlantic blocking with limited observational dataCode0
E3: Ensemble of Expert Embedders for Adapting Synthetic Image Detectors to New Generators Using Limited DataCode0
Convolutional neural network classification of cancer cytopathology images: taking breast cancer as an example—0
MSciNLI: A Diverse Benchmark for Scientific Natural Language InferenceCode0
GLID: Pre-training a Generalist Encoder-Decoder Vision Model—0
Depth Estimation using Weighted-loss and Transfer Learning—0
Predictive Handover Strategy in 6G and Beyond: A Deep and Transfer Learning Approach—0
We're Calling an Intervention: Exploring Fundamental Hurdles in Adapting Language Models to Nonstandard TextCode0
XNLIeu: a dataset for cross-lingual NLI in BasqueCode0
Spatial Transfer Learning for Estimating PM2.5 in Data-poor RegionsCode0
The Sandwich meta-framework for architecture agnostic deep privacy-preserving transfer learning for non-invasive brainwave decoding—0
Event Extraction in Basque: Typologically motivated Cross-Lingual Transfer-Learning Analysis—0
The impact of data set similarity and diversity on transfer learning success in time series forecasting—0
Using Few-Shot Learning to Classify Primary Lung Cancer and Other Malignancy with Lung Metastasis in Cytological Imaging via Endobronchial Ultrasound Procedures—0
Supervised Gradual Machine Learning for Aspect Category Detection—0
BatSort: Enhanced Battery Classification with Transfer Learning for Battery Sorting and RecyclingCode0
Joint Identifiability of Cross-Domain Recommendation via Hierarchical Subspace Disentanglement—0
VoltaVision: A Transfer Learning model for electronic component classificationCode0
Enhancing Breast Cancer Diagnosis in Mammography: Evaluation and Integration of Convolutional Neural Networks and Explainable AI—0
Teaching Llama a New Language Through Cross-Lingual Knowledge TransferCode0
How does Multi-Task Training Affect Transformer In-Context Capabilities? Investigations with Function ClassesCode0
ANGOFA: Leveraging OFA Embedding Initialization and Synthetic Data for Angolan Language ModelCode0
Transfer learning applications for anomaly detection in wind turbines—0
Lifelong Event Detection with Embedding Space Separation and Compaction—0
What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and BiasesCode0
Cross-Architecture Transfer Learning for Linear-Cost Inference Transformers—0
Active Exploration in Bayesian Model-based Reinforcement Learning for Robot Manipulation—0
R^2-Tuning: Efficient Image-to-Video Transfer Learning for Video Temporal Grounding—0
ImageNot: A contrast with ImageNet preserves model rankingsCode0
Federated Distillation: A Survey—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