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 21–30 of 265 papers

TitleStatusHype
Take Package as Language: Anomaly Detection Using TransformerCode0
DepthSplat: Connecting Gaussian Splatting and DepthCode5
SynCo: Synthetic Hard Negatives in Contrastive Learning for Better Unsupervised Visual RepresentationsCode0
Calibrating Language Models with Adaptive Temperature ScalingCode0
Range-aware Positional Encoding via High-order Pretraining: Theory and Practice—0
GFlowNet Pretraining with Inexpensive Rewards—0
TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training—0
PersonViT: Large-scale Self-supervised Vision Transformer for Person Re-IdentificationCode1
From Recognition to Prediction: Leveraging Sequence Reasoning for Action AnticipationCode0
Large Language Model Enabled Semantic Communication Systems—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