SOTAVerified

Unsupervised Pre-training

Pre-training a neural network using unsupervised (self-supervised) auxiliary tasks on unlabeled data.

Papers

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Showing 211–220 of 265 papers

TitleStatusHype
Extractive NarrativeQA with Heuristic Pre-Training—0
Unsupervised pre-training for sequence to sequence speech recognition—0
Pre-train and Learn: Preserve Global Information for Graph Neural NetworksCode0
Improving Transformer-based Speech Recognition Using Unsupervised Pre-trainingCode1
Extracting UMLS Concepts from Medical Text Using General and Domain-Specific Deep Learning Models—0
SMiRL: Surprise Minimizing RL in Entropic Environments—0
Understanding Semantics from Speech Through Pre-training—0
Bridging the domain gap in cross-lingual document classificationCode0
Effective training of deep convolutional neural networks for hyperspectral image classification through artificial labeling—0
Cross-Domain Training for Goal-Oriented Conversational Agents—0
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All datasetsMeaslesUCI measles

Benchmark Results

#ModelMetricClaimedVerifiedStatus
115RDLsAccuracy (%)95—Unverified
29RDLsAccuracy (%)94—Unverified
33 RMDLAccuracy (%)93—Unverified
4CNNAccuracy (%)73—Unverified
5RMDLAccuracy (%)0.1—Unverified
#ModelMetricClaimedVerifiedStatus
1RMDL (30 RDLs)Sensitivity (VEB)90.69—Unverified
2Sensitivity89.1—Unverified
3RMDL 3 RDLsSensitivity0.87—Unverified