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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 376–400 of 10307 papers

Title	Date	Tasks	Status	Hype
Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data	Apr 11, 2022	Inference AttackMembership Inference Attack	CodeCode Available	1
Common Voice: A Massively-Multilingual Speech Corpus	Dec 13, 2019	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1
Communication-Efficient and Privacy-Preserving Feature-based Federated Transfer Learning	Sep 12, 2022	Federated Learningimage-classification	CodeCode Available	1
Composable Sparse Fine-Tuning for Cross-Lingual Transfer	Oct 14, 2021	Cross-Lingual TransferLanguage Modeling	CodeCode Available	1
Compositional Language Continual Learning	May 1, 2020	Continual LearningMachine Translation	CodeCode Available	1
Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning	Feb 19, 2020	Transfer Learning	CodeCode Available	1
Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup	Dec 17, 2020	InformativenessKnowledge Distillation	CodeCode Available	1
Automatic identification of segmentation errors for radiotherapy using geometric learning	Jun 27, 2022	Graph Neural NetworkSelf-Supervised Learning	CodeCode Available	1
AFEC: Active Forgetting of Negative Transfer in Continual Learning	Oct 23, 2021	Continual LearningTransfer Learning	CodeCode Available	1
AutoTune: Automatically Tuning Convolutional Neural Networks for Improved Transfer Learning	Apr 25, 2020	Bayesian OptimizationTransfer Learning	CodeCode Available	1
ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine Translation	Dec 8, 2022	Low Resource Neural Machine TranslationLow-Resource Neural Machine Translation	CodeCode Available	1
Continual learning with hypernetworks	Jun 3, 2019	Continual LearningTransfer Learning	CodeCode Available	1
Context-Transformer: Tackling Object Confusion for Few-Shot Detection	Mar 16, 2020	DiversityFew-Shot Learning	CodeCode Available	1
Automated Cloud Provisioning on AWS using Deep Reinforcement Learning	Sep 13, 2017	Cloud ComputingDeep Reinforcement Learning	CodeCode Available	1
AD-KD: Attribution-Driven Knowledge Distillation for Language Model Compression	May 17, 2023	Knowledge DistillationLanguage Modeling	CodeCode Available	1
Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity	Sep 6, 2020	NMTTransfer Learning	CodeCode Available	1
AD-L-JEPA: Self-Supervised Spatial World Models with Joint Embedding Predictive Architecture for Autonomous Driving with LiDAR Data	Jan 9, 2025	3D Object DetectionAutonomous Driving	CodeCode Available	1
Continual Sequence Generation with Adaptive Compositional Modules	Mar 20, 2022	Continual LearningTransfer Learning	CodeCode Available	1
Contour Knowledge Transfer for Salient Object Detection	Sep 1, 2018	Contour DetectionObject	CodeCode Available	1
A Convolutional LSTM based Residual Network for Deepfake Video Detection	Sep 16, 2020	DeepFake DetectionFace Swapping	CodeCode Available	1
Contrastive Embeddings for Neural Architectures	Feb 8, 2021	Contrastive LearningNeural Architecture Search	CodeCode Available	1
Contrastive Representation Distillation	Oct 23, 2019	Contrastive LearningKnowledge Distillation	CodeCode Available	1
Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets	Aug 15, 2022	Transfer Learning	CodeCode Available	1
Cooperative Self-training of Machine Reading Comprehension	Mar 12, 2021	Extractive Question-AnsweringMachine Reading Comprehension	CodeCode Available	1
Auxiliary Signal-Guided Knowledge Encoder-Decoder for Medical Report Generation	Jun 6, 2020	DecoderImage Captioning	CodeCode Available	1

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All datasets Office-Home 100 sleep nights of 8 caregivers BanglaLekha Isolated Dataset COCO70 KITTI Object Tracking Evaluation 2012 Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	APCLIP	Accuracy	84.2	—	Unverified
2	DFA-ENT	Accuracy	69.2	—	Unverified
3	DFA-SAFN	Accuracy	69.1	—	Unverified
4	EasyTL	Accuracy	63.3	—	Unverified
5	MEDA	Accuracy	60.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN	10-20% Mask PSNR	3.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Chatterjee, Dutta et al.[1]	Accuracy	96.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Co-Tuning	Accuracy	85.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Physical Access	EER	5.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	riadd.aucmedi	AUROC	0.95	—	Unverified