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 1351–1400 of 10307 papers

TitleStatusHype
A Competition Winning Deep Reinforcement Learning Agent in microRTSCode1
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning ProcessesCode1
Less Could Be Better: Parameter-efficient Fine-tuning Advances Medical Vision Foundation ModelsCode1
Less is More: Lighter and Faster Deep Neural Architecture for Tomato Leaf Disease ClassificationCode1
CLIP meets GamePhysics: Towards bug identification in gameplay videos using zero-shot transfer learningCode1
Leverage Your Local and Global Representations: A New Self-Supervised Learning StrategyCode1
Leveraging Predicate and Triplet Learning for Scene Graph GenerationCode1
Leveraging Seen and Unseen Semantic Relationships for Generative Zero-Shot LearningCode1
A Strong and Simple Deep Learning Baseline for BCI MI DecodingCode1
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task LearningCode1
CLIP-Lite: Information Efficient Visual Representation Learning with Language SupervisionCode1
Lifelong Embedding Learning and Transfer for Growing Knowledge GraphsCode1
CLIP-VG: Self-paced Curriculum Adapting of CLIP for Visual GroundingCode1
Class-relation Knowledge Distillation for Novel Class DiscoveryCode1
Classification of Large-Scale High-Resolution SAR Images with Deep Transfer LearningCode1
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label NoiseCode1
LLM-Neo: Parameter Efficient Knowledge Distillation for Large Language ModelsCode1
Load Forecasting for Households and Energy Communities: Are Deep Learning Models Worth the Effort?Code1
LogME: Practical Assessment of Pre-trained Models for Transfer LearningCode1
Long-Context Inference with Retrieval-Augmented Speculative DecodingCode1
Association Graph Learning for Multi-Task Classification with Category ShiftsCode1
LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge RecoveryCode1
Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural NetworksCode1
Low Resource Neural Machine Translation: A Benchmark for Five African LanguagesCode1
Classification of Epithelial Ovarian Carcinoma Whole-Slide Pathology Images Using Deep Transfer LearningCode1
M-ABSA: A Multilingual Dataset for Aspect-Based Sentiment AnalysisCode1
Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 LanguagesCode1
Malaria Parasite Detection using Efficient Neural EnsemblesCode1
ManyModalQA: Modality Disambiguation and QA over Diverse InputsCode1
Many-to-English Machine Translation Tools, Data, and Pretrained ModelsCode1
Anatomical Foundation Models for Brain MRIsCode1
CLiMB: A Continual Learning Benchmark for Vision-and-Language TasksCode1
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIPCode1
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning ParadigmsCode1
MatchSeg: Towards Better Segmentation via Reference Image MatchingCode1
Materials Representation and Transfer Learning for Multi-Property PredictionCode1
A Comprehensive Approach for UAV Small Object Detection with Simulation-based Transfer Learning and Adaptive FusionCode1
BARThez: a Skilled Pretrained French Sequence-to-Sequence ModelCode1
MEBeauty: a multi-ethnic facial beauty dataset in-the-wildCode1
Med3D: Transfer Learning for 3D Medical Image AnalysisCode1
ChrEn: Cherokee-English Machine Translation for Endangered Language RevitalizationCode1
Melanoma Detection using Adversarial Training and Deep Transfer LearningCode1
Memory Efficient Meta-Learning with Large ImagesCode1
Enhanced Gaussian Process Dynamical Models with Knowledge Transfer for Long-term Battery Degradation ForecastingCode1
Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image ClassificationCode1
Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-ExpertsCode1
MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and ArchitecturesCode1
MetaSleepLearner: A Pilot Study on Fast Adaptation of Bio-signals-Based Sleep Stage Classifier to New Individual Subject Using Meta-LearningCode1
Meta-Transfer Learning for Zero-Shot Super-ResolutionCode1
Chip Placement with Deep Reinforcement LearningCode1
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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