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 71–80 of 265 papers

TitleStatusHype
Semi-Supervised Semantic Segmentation of Cell Nuclei via Diffusion-based Large-Scale Pre-Training and Collaborative Learning—0
Towards General Text Embeddings with Multi-stage Contrastive Learning—0
HIQL: Offline Goal-Conditioned RL with Latent States as ActionsCode1
Disentangling Node Attributes from Graph Topology for Improved Generalizability in Link Prediction—0
ECGBERT: Understanding Hidden Language of ECGs with Self-Supervised Representation Learning—0
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement LearningCode1
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human FeedbackCode0
Rethinking Semi-supervised Learning with Language ModelsCode1
PTGB: Pre-Train Graph Neural Networks for Brain Network AnalysisCode1
LATTE: Label-efficient Incident Phenotyping from Longitudinal Electronic Health RecordsCode0
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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