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 7651–7700 of 10307 papers

TitleStatusHype
Transfer learning to model inertial confinement fusion experiments—0
Transfer Learning under High-dimensional Generalized Linear Models—0
Transfer Learning Under High-Dimensional Graph Convolutional Regression Model for Node Classification—0
Transfer Learning Under High-Dimensional Network Convolutional Regression Model—0
Transfer Learning using CNN for Handwritten Devanagari Character Recognition—0
Transfer Learning Using Logistic Regression in Credit Scoring—0
Transfer Learning using Neural Ordinary Differential Equations—0
Transfer Learning using Representation Learning in Massive Open Online Courses—0
Using different sources of ground truths and transfer learning to improve the generalization of photometric redshift estimation—0
The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection—0
The SLT-Interactions Parsing System at the CoNLL 2018 Shared Task—0
The SpeakIn Speaker Verification System for Far-Field Speaker Verification Challenge 2022—0
The Specificity and Helpfulness of Peer-to-Peer Feedback in Higher Education—0
Text-based automatic personality prediction: A bibliographic review—0
The UCF Systems for the LoResMT 2021 Machine Translation Shared Task—0
The Universitat d'Alacant Submissions to the English-to-Kazakh News Translation Task at WMT 2019—0
The University of Helsinki Submission to the IWSLT2020 Offline SpeechTranslation Task—0
The University of Maryland's Kazakh-English Neural Machine Translation System at WMT19—0
The Utility of General Domain Transfer Learning for Medical Language Tasks—0
The Wisdom of a Crowd of Brains: A Universal Brain Encoder—0
The Word Analogy Testing Caveat—0
ThinkLess: A Training-Free Inference-Efficient Method for Reducing Reasoning Redundancy—0
Think Small, Act Big: Primitive Prompt Learning for Lifelong Robot Manipulation—0
This joke is [MASK]: Recognizing Humor and Offense with Prompting—0
Threat Classification on Deployed Optical Networks Using MIMO Digital Fiber Sensing, Wavelets, and Machine Learning—0
Through the Thicket: A Study of Number-Oriented LLMs derived from Random Forest Models—0
TIAGo RL: Simulated Reinforcement Learning Environments with Tactile Data for Mobile Robots—0
Tiered Graph Autoencoders with PyTorch Geometric for Molecular Graphs—0
Tight Rates in Supervised Outlier Transfer Learning—0
Time-Frequency Analysis based Blind Modulation Classification for Multiple-Antenna Systems—0
Time Series Anomaly Detection Using Convolutional Neural Networks and Transfer Learning—0
Time-Series Domain Adaptation via Sparse Associative Structure Alignment: Learning Invariance and Variance—0
Time Series Predictions in Unmonitored Sites: A Survey of Machine Learning Techniques in Water Resources—0
Time-Variant Variational Transfer for Value Functions—0
Tiny-Attention Adapter: Contexts Are More Important Than the Number of Parameters—0
TinyFedTL: Federated Transfer Learning on Tiny Devices—0
TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation—0
TIPAA-SSL: Text Independent Phone-to-Audio Alignment based on Self-Supervised Learning and Knowledge Transfer—0
Tissue-Contrastive Semi-Masked Autoencoders for Segmentation Pretraining on Chest CT—0
Tissue Segmentation of Thick-Slice Fetal Brain MR Scans with Guidance from High-Quality Isotropic Volumes—0
TITAN: T Cell Receptor Specificity Prediction with Bimodal Attention Networks—0
TLCE: Transfer-Learning Based Classifier Ensembles for Few-Shot Class-Incremental Learning—0
Transmission Line Defect Detection Based on UAV Patrol Images and Vision-language Pretraining—0
TLETA: Deep Transfer Learning and Integrated Cellular Knowledge for Estimated Time of Arrival Prediction—0
TLMCM Network for Medical Image Hierarchical Multi-Label Classification—0
TL-PCA: Transfer Learning of Principal Component Analysis—0
TL-SDD: A Transfer Learning-Based Method for Surface Defect Detection with Few Samples—0
TLU-Net: A Deep Learning Approach for Automatic Steel Surface Defect Detection—0
To believe or not to believe: Validating explanation fidelity for dynamic malware analysis—0
Toddler-Guidance Learning: Impacts of Critical Period on Multimodal AI Agents—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