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 51–75 of 265 papers

TitleStatusHype
SeCo: Exploring Sequence Supervision for Unsupervised Representation LearningCode1
SEED: Self-supervised Distillation For Visual RepresentationCode1
Initialization and Regularization of Factorized Neural LayersCode1
Bag of Tricks and A Strong baseline for Image Copy DetectionCode1
Behavior From the Void: Unsupervised Active Pre-TrainingCode1
D^2LV: A Data-Driven and Local-Verification Approach for Image Copy DetectionCode1
Exact solutions to the nonlinear dynamics of learning in deep linear neural networksCode1
SPACE: Your Genomic Profile Predictor is a Powerful DNA Foundation ModelCode1
TACRED Revisited: A Thorough Evaluation of the TACRED Relation Extraction TaskCode1
The CLEAR Benchmark: Continual LEArning on Real-World ImageryCode1
Unsupervised Pre-Training For Data-Efficient Text-to-Speech On Low Resource LanguagesCode1
BMRetriever: Tuning Large Language Models as Better Biomedical Text RetrieversCode1
FreePoint: Unsupervised Point Cloud Instance SegmentationCode1
Exploring the Limits of Out-of-Distribution DetectionCode1
ELECTRIcity: An Efficient Transformer for Non-Intrusive Load MonitoringCode1
FedAUX: Leveraging Unlabeled Auxiliary Data in Federated LearningCode1
DOBF: A Deobfuscation Pre-Training Objective for Programming LanguagesCode1
DocILE Benchmark for Document Information Localization and ExtractionCode1
Don't Stop Pretraining? Make Prompt-based Fine-tuning Powerful LearnerCode1
Image Representations Learned With Unsupervised Pre-Training Contain Human-like BiasesCode1
Korean-Specific Dataset for Table Question AnsweringCode1
MultiTalent: A Multi-Dataset Approach to Medical Image SegmentationCode1
RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object DetectionCode1
Leveraging Pre-trained Checkpoints for Sequence Generation TasksCode1
Unsupervised Semantic Segmentation by Contrasting Object Mask ProposalsCode1
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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