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 351–400 of 10307 papers

TitleStatusHype
Can LLMs' Tuning Methods Work in Medical Multimodal Domain?Code1
Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?Code1
A Data-Based Perspective on Transfer LearningCode1
BadMerging: Backdoor Attacks Against Model MergingCode1
A Comprehensive Study on Torchvision Pre-trained Models for Fine-grained Inter-species ClassificationCode1
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly LocalizationCode1
Chaos as an interpretable benchmark for forecasting and data-driven modellingCode1
Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric ModelsCode1
AVocaDo: Strategy for Adapting Vocabulary to Downstream DomainCode1
CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel SynthesisCode1
Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural NetworksCode1
Classification of Epithelial Ovarian Carcinoma Whole-Slide Pathology Images Using Deep Transfer LearningCode1
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning ProcessesCode1
CLiMB: A Continual Learning Benchmark for Vision-and-Language TasksCode1
A Whisper transformer for audio captioning trained with synthetic captions and transfer learningCode1
CLIP-Lite: Information Efficient Visual Representation Learning with Language SupervisionCode1
Bag of Tricks for Image Classification with Convolutional Neural NetworksCode1
A Deep Learning-Based Supervised Transfer Learning Framework for DOA Estimation with Array ImperfectionsCode1
Bert4XMR: Cross-Market Recommendation with Bidirectional Encoder Representations from TransformerCode1
Clustered Hierarchical Anomaly and Outlier Detection AlgorithmsCode1
A deep learning framework for solution and discovery in solid mechanicsCode1
CODE-AE: A Coherent De-confounding Autoencoder for Predicting Patient-Specific Drug Response From Cell Line TranscriptomicsCode1
A Comprehensive Survey on Transfer LearningCode1
CodeTrans: Towards Cracking the Language of Silicon's Code Through Self-Supervised Deep Learning and High Performance ComputingCode1
Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement LearningCode1
Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic DataCode1
Common Voice: A Massively-Multilingual Speech CorpusCode1
Communication-Efficient and Privacy-Preserving Feature-based Federated Transfer LearningCode1
Composable Sparse Fine-Tuning for Cross-Lingual TransferCode1
Compositional Language Continual LearningCode1
Compressing BERT: Studying the Effects of Weight Pruning on Transfer LearningCode1
Computation-Efficient Knowledge Distillation via Uncertainty-Aware MixupCode1
Automatic identification of segmentation errors for radiotherapy using geometric learningCode1
AFEC: Active Forgetting of Negative Transfer in Continual LearningCode1
AutoTune: Automatically Tuning Convolutional Neural Networks for Improved Transfer LearningCode1
ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine TranslationCode1
Continual learning with hypernetworksCode1
Context-Transformer: Tackling Object Confusion for Few-Shot DetectionCode1
Automated Cloud Provisioning on AWS using Deep Reinforcement LearningCode1
AD-KD: Attribution-Driven Knowledge Distillation for Language Model CompressionCode1
Automatic Dialect Adaptation in Finnish and its Effect on Perceived CreativityCode1
AD-L-JEPA: Self-Supervised Spatial World Models with Joint Embedding Predictive Architecture for Autonomous Driving with LiDAR DataCode1
Continual Sequence Generation with Adaptive Compositional ModulesCode1
Contour Knowledge Transfer for Salient Object DetectionCode1
A Convolutional LSTM based Residual Network for Deepfake Video DetectionCode1
Contrastive Embeddings for Neural ArchitecturesCode1
Contrastive Representation DistillationCode1
Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNetsCode1
Cooperative Self-training of Machine Reading ComprehensionCode1
Auxiliary Signal-Guided Knowledge Encoder-Decoder for Medical Report GenerationCode1
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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