SOTAVerified

Unsupervised Pre-training

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 211–220 of 265 papers

TitleStatusHype
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback—0
Large Language Model Enabled Semantic Communication Systems—0
Latte: Transfering LLMs` Latent-level Knowledge for Few-shot Tabular Learning—0
Learning Discriminative Features with Class Encoder—0
Learning Non-Linear Reconstruction Models for Image Set Classification—0
Learning Unsupervised Gaze Representation via Eye Mask Driven Information Bottleneck—0
Leveraging Random Label Memorization for Unsupervised Pre-Training—0
Lottery Hypothesis based Unsupervised Pre-training for Model Compression in Federated Learning—0
Machine Translation Pre-training for Data-to-Text Generation - A Case Study in Czech—0
Masked Feature Modelling: Feature Masking for the Unsupervised Pre-training of a Graph Attention Network Block for Bottom-up Video Event Recognition—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