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 8426–8450 of 10307 papers

TitleStatusHype
Open Relation Extraction: Relational Knowledge Transfer from Supervised Data to Unsupervised DataCode0
Cross-Task Knowledge Transfer for Query-Based Text Summarization—0
Cross-Cultural Transfer Learning for Text Classification—0
Cross-lingual Transfer Learning with Data Selection for Large-Scale Spoken Language Understanding—0
NSIT@NLP4IF-2019: Propaganda Detection from News Articles using Transfer Learning—0
Contextualized Cross-Lingual Event Trigger Extraction with Minimal Resources—0
Sentence-Level Propaganda Detection in News Articles with Transfer Learning and BERT-BiLSTM-Capsule Model—0
Natural Language Generation for Effective Knowledge DistillationCode0
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
Region-based Convolution Neural Network Approach for Accurate Segmentation of Pelvic Radiograph—0
Cross lingual transfer learning for zero-resource domain adaptation—0
Attention-Gated Graph Convolutions for Extracting Drug Interaction Information from Drug Labels—0
Adversarial Multitask Learning for Joint Multi-Feature and Multi-Dialect Morphological Modeling—0
A BERT-Based Transfer Learning Approach for Hate Speech Detection in Online Social MediaCode0
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
Exploring Multilingual Syntactic Sentence RepresentationsCode0
Secost: Sequential co-supervision for large scale weakly labeled audio event detection—0
The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection—0
Unsupervised Representation Learning with Future Observation Prediction for Speech Emotion Recognition—0
Knowledge Transfer between Datasets for Learning-based Tissue Microstructure Estimation—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