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 951–1000 of 10307 papers

TitleStatusHype
EEV: A Large-Scale Dataset for Studying Evoked Expressions from VideoCode1
Multilingual Knowledge Graph Completion via Ensemble Knowledge TransferCode1
Dynamic Domain Adaptation for Efficient InferenceCode1
MultiLoKo: a multilingual local knowledge benchmark for LLMs spanning 31 languagesCode1
Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural NetworksCode1
Multimodal Parameter-Efficient Few-Shot Class Incremental LearningCode1
MV-Adapter: Multimodal Video Transfer Learning for Video Text RetrievalCode1
Multinational Address Parsing: A Zero-Shot EvaluationCode1
Audio Spoofing Verification using Deep Convolutional Neural Networks by Transfer LearningCode1
ArMATH: a Dataset for Solving Arabic Math Word ProblemsCode1
Detection and Classification of Diabetic Retinopathy using Deep Learning Algorithms for Segmentation to Facilitate Referral Recommendation for Test and Treatment PredictionCode1
Reasoning Visual Dialog with Sparse Graph Learning and Knowledge TransferCode1
Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural NetworksCode1
Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous ControlCode1
Determining Chess Game State From an ImageCode1
Developing a Named Entity Recognition Dataset for TagalogCode1
EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP ApplicationsCode1
A transfer learning based approach for pronunciation scoringCode1
Accurate Clinical Toxicity Prediction using Multi-task Deep Neural Nets and Contrastive Molecular ExplanationsCode1
Mutual Contrastive Learning for Visual Representation LearningCode1
Effect of Pre-Training Scale on Intra- and Inter-Domain Full and Few-Shot Transfer Learning for Natural and Medical X-Ray Chest ImagesCode1
NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and ColonoscopyCode1
ArtNeRF: A Stylized Neural Field for 3D-Aware Cartoonized Face SynthesisCode1
ARWKV: Pretrain is not what we need, an RNN-Attention-Based Language Model Born from TransformerCode1
Efficient Fine-tuning of Audio Spectrogram Transformers via Soft Mixture of AdaptersCode1
A Scalable and Generalizable Pathloss Map PredictionCode1
A Further Study of Unsupervised Pre-training for Transformer Based Speech RecognitionCode1
Neural Incompatibility: The Unbridgeable Gap of Cross-Scale Parametric Knowledge Transfer in Large Language ModelsCode1
A fuzzy distance-based ensemble of deep models for cervical cancer detectionCode1
Differencing based Self-supervised pretraining for Scene Change DetectionCode1
aschern at SemEval-2020 Task 11: It Takes Three to Tango: RoBERTa, CRF, and Transfer LearningCode1
Neural Topic Modeling with Continual Lifelong LearningCode1
Diffusion Models Beat GANs on Image ClassificationCode1
Diffusion Model as Representation LearnerCode1
End-to-end lyrics Recognition with Voice to Singing Style TransferCode1
Adapting LLaMA Decoder to Vision TransformerCode1
AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an AppCode1
Non-binary deep transfer learning for image classificationCode1
Novel Class Discovery for Ultra-Fine-Grained Visual CategorizationCode1
Novel Scenes & Classes: Towards Adaptive Open-set Object DetectionCode1
Dual-Teacher++: Exploiting Intra-domain and Inter-domain Knowledge with Reliable Transfer for Cardiac SegmentationCode1
Distance-Based Regularisation of Deep Networks for Fine-TuningCode1
Disentangled Pre-training for Human-Object Interaction DetectionCode1
Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer LearningCode1
Distilling Knowledge from Graph Convolutional NetworksCode1
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighterCode1
A Simple and Effective Approach to Automatic Post-Editing with Transfer LearningCode1
A Simple and Effective Approach to Automatic Post-Editing with Transfer LearningCode1
A Text Classification-Based Approach for Evaluating and Enhancing the Machine Interpretability of Building CodesCode1
A Systematic Benchmarking Analysis of Transfer Learning for Medical Image AnalysisCode1
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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