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 7451–7500 of 10307 papers

TitleStatusHype
Distilling Structured Knowledge for Text-Based Relational Reasoning—0
Efficient Transfer Learning for Quality Estimation with Bottleneck Adapter Layer—0
Cancer Registry Information Extraction via Transfer Learning—0
Linguist Geeks on WNUT-2020 Task 2: COVID-19 Informative Tweet Identification using Progressive Trained Language Models and Data Augmentation—0
The NiuTrans System for the WMT20 Quality Estimation Shared Task—0
The Amazing World of Neural Language Generation—0
SciWING– A Software Toolkit for Scientific Document Processing—0
``I'd rather just go to bed'': Understanding Indirect Answers—0
How Far Can We Go with Data Selection? A Case Study on Semantic Sequence Tagging Tasks—0
WLV-RIT at HASOC-Dravidian-CodeMix-FIRE2020: Offensive Language Identification in Code-switched YouTube Comments—0
Unified Humor Detection Based on Sentence-pair Augmentation and Transfer Learning—0
UET at WNUT-2020 Task 2: A Study of Combining Transfer Learning Methods for Text Classification with RoBERTa—0
Transfer Learning for Related Languages: Submissions to the WMT20 Similar Language Translation Task—0
Zero-Shot Rationalization by Multi-Task Transfer Learning from Question AnsweringCode0
Multimodal and self-supervised representation learning for automatic gesture recognition in surgical robotics—0
Is Transfer Learning Necessary for Protein Landscape Prediction?—0
Automatic Chronic Degenerative Diseases Identification Using Enteric Nervous System ImagesCode0
Free the Plural: Unrestricted Split-Antecedent Anaphora ResolutionCode0
C-Net: A Reliable Convolutional Neural Network for Biomedical Image ClassificationCode0
Multi-stage transfer learning for lung segmentation using portable X-ray devices for patients with COVID-19—0
Speech-Image Semantic Alignment Does Not Depend on Any Prior Classification Tasks—0
A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation—0
Transfer Learning improves MI BCI models classification accuracy in Parkinson's disease patients—0
Polymer Informatics with Multi-Task Learning—0
Augmenting transferred representations for stock classification—0
Accurate Prostate Cancer Detection and Segmentation on Biparametric MRI using Non-local Mask R-CNN with Histopathological Ground Truth—0
Exploring the potential of transfer learning for metamodels of heterogeneous material deformationCode0
Learning to be Safe: Deep RL with a Safety Critic—0
Behavior Priors for Efficient Reinforcement Learning—0
FaceLeaks: Inference Attacks against Transfer Learning Models via Black-box Queries—0
CopyPaste: An Augmentation Method for Speech Emotion Recognition—0
Multi-Class Zero-Shot Learning for Artistic Material Recognition—0
Transfer Learning for Input Estimation of Vehicle Systems—0
Smartphone-Based Test and Predictive Models for Rapid, Non-Invasive, and Point-of-Care Monitoring of Ocular and Cardiovascular Complications Related to Diabetes—0
A Survey on Curriculum Learning—0
On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning—0
Multilingual Speech Translation with Efficient Finetuning of Pretrained Models—0
Shared Space Transfer Learning for analyzing multi-site fMRI data—0
Unsupervised Paraphrasing with Pretrained Language Models—0
When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language ModelsCode0
Towards Fair Knowledge Transfer for Imbalanced Domain Adaptation—0
Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few LabelsCode0
Anchor-based Bilingual Word Embeddings for Low-Resource Languages—0
Improving Classification through Weak Supervision in Context-specific Conversational Agent Development for Teacher Education—0
A Combinatorial Perspective on Transfer LearningCode0
A Study of Transfer Learning in Music Source Separation—0
Learning Transferrable Parameters for Long-tailed Sequential User Behavior Modeling—0
CUNI Systems for the Unsupervised and Very Low Resource Translation Task in WMT20—0
Network Anomaly Detection Using Federated Learning and Transfer Learning—0
Multilingual Approach to Joint Speech and Accent Recognition with DNN-HMM Framework—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