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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3151–3175 of 10307 papers

TitleStatusHype
Self-supervised Pre-training of Text RecognizersCode0
Koopman-based Deep Learning for Nonlinear System Estimation—0
Employing Federated Learning for Training Autonomous HVAC Systems—0
ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents—0
Why does Knowledge Distillation Work? Rethink its Attention and Fidelity MechanismCode0
Let's Focus: Focused Backdoor Attack against Federated Transfer Learning—0
Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray ClassificationCode0
Task and Domain Adaptive Reinforcement Learning for Robot ControlCode0
What Drives Performance in Multilingual Language Models?Code0
Generation of Uncorrelated Residual Variables for Chemical Process Fault Diagnosis via Transfer Learning-based Input-Output Decoupled Network—0
Context Matters: Leveraging Spatiotemporal Metadata for Semi-Supervised Learning on Remote Sensing ImagesCode0
Enhancing Action Recognition from Low-Quality Skeleton Data via Part-Level Knowledge Distillation—0
Transfer Learning and Transformer Architecture for Financial Sentiment Analysis—0
EkoHate: Abusive Language and Hate Speech Detection for Code-switched Political Discussions on Nigerian TwitterCode0
Toxicity Classification in Ukrainian—0
Transfer Learning Enhanced Single-choice Decision for Multi-choice Question Answering—0
Remote Sensing Image Enhancement through Spatiotemporal Filtering—0
2M-NER: Contrastive Learning for Multilingual and Multimodal NER with Language and Modal Fusion—0
Comparison of self-supervised in-domain and supervised out-domain transfer learning for bird species recognition—0
Causally Abstracted Multi-armed BanditsCode0
A Novel Spike Transformer Network for Depth Estimation from Event Cameras via Cross-modality Knowledge Distillation—0
FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings via Deep Neural NetworksCode0
Federated Transfer Component Analysis Towards Effective VNF Profiling—0
Knowledge Transfer for Cross-Domain Reinforcement Learning: A Systematic Review—0
Self-supervised visual learning in the low-data regime: a comparative evaluation—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