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 8351–8400 of 10307 papers

TitleStatusHype
Transfer Learning in Biomedical Named Entity Recognition: An Evaluation of BERT in the PharmaCoNER task—0
Transfer Learning from Transformers to Fake News Challenge Stance Detection (FNC-1) Task—0
Positional Attention-based Frame Identification with BERT: A Deep Learning Approach to Target Disambiguation and Semantic Frame Selection—0
Naver Labs Europe's Systems for the Document-Level Generation and Translation Task at WNGT 2019—0
Cross lingual transfer learning for zero-resource domain adaptation—0
Region-based Convolution Neural Network Approach for Accurate Segmentation of Pelvic Radiograph—0
Attention-Gated Graph Convolutions for Extracting Drug Interaction Information from Drug Labels—0
A BERT-Based Transfer Learning Approach for Hate Speech Detection in Online Social MediaCode0
Adversarial Multitask Learning for Joint Multi-Feature and Multi-Dialect Morphological Modeling—0
Thieves on Sesame Street! Model Extraction of BERT-based APIsCode0
Decoding Neural Responses in Mouse Visual Cortex through a Deep Neural NetworkCode0
FineText: Text Classification via Attention-based Language Model Fine-tuning—0
Secost: Sequential co-supervision for large scale weakly labeled audio event detection—0
Exploring Multilingual Syntactic Sentence RepresentationsCode0
The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection—0
Deep Learning of Subsurface Flow via Theory-guided Neural Network—0
Unsupervised Representation Learning with Future Observation Prediction for Speech Emotion Recognition—0
Animal Detection in Man-made EnvironmentsCode0
Knowledge Transfer between Datasets for Learning-based Tissue Microstructure Estimation—0
Generative Pre-Training for Speech with Autoregressive Predictive CodingCode1
Class-imbalanced Domain Adaptation: An Empirical Odyssey—0
Semantic Segmentation of Skin Lesions using a Small Data Set—0
Contrastive Representation DistillationCode1
Hierarchical Transformers for Long Document ClassificationCode1
Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules—0
Healthcare NER Models Using Language Model Pretraining—0
Exploring the Limits of Transfer Learning with a Unified Text-to-Text TransformerCode2
Semi-Supervised Histology Classification using Deep Multiple Instance Learning and Contrastive Predictive Coding—0
Kernel computations from large-scale random features obtained by Optical Processing UnitsCode0
Word-level Embeddings for Cross-Task Transfer Learning in Speech ProcessingCode0
Transformer-CNN: Fast and Reliable tool for QSARCode0
Multiphase flow prediction with deep neural networks—0
Localization of Fake News Detection via Multitask Transfer LearningCode0
Decoupling Representation and Classifier for Long-Tailed RecognitionCode1
PT-CoDE: Pre-trained Context-Dependent Encoder for Utterance-level Emotion RecognitionCode1
Online Bagging for Anytime Transfer Learning—0
Evolutionary Dynamic Multi-objective Optimization Via Regression Transfer Learning—0
Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCICode0
Understanding Social Networks using Transfer Learning—0
Conservation AI: Live Stream Analysis for the Detection of Endangered Species Using Convolutional Neural Networks and Drone Technology—0
Evolution of transfer learning in natural language processing—0
Analyzing the Forgetting Problem in the Pretrain-Finetuning of Dialogue Response Models—0
Transfer Learning for Algorithm Recommendation—0
RiWalk: Fast Structural Node Embedding via Role IdentificationCode0
Adaptive Transfer Learning of Multi-View Time Series Classification—0
Actor Critic with Differentially Private Critic—0
Manifold Embedded Knowledge Transfer for Brain-Computer InterfacesCode0
Self-supervised Label Augmentation via Input TransformationsCode0
Training Compact Models for Low Resource Entity Tagging using Pre-trained Language Models—0
Two-sample Testing Using Deep LearningCode0
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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