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 176–200 of 265 papers

TitleStatusHype
Accelerating Training of Transformer-Based Language Models with Progressive Layer DroppingCode0
Unsupervised Vision-and-Language Pre-training Without Parallel Images and CaptionsCode1
GiBERT: Introducing Linguistic Knowledge into BERT through a Lightweight Gated Injection Method—0
Pre-training Graph Transformer with Multimodal Side Information for Recommendation—0
Self-training and Pre-training are Complementary for Speech RecognitionCode0
Corruption Is Not All Bad: Incorporating Discourse Structure into Pre-training via Corruption for Essay Scoring—0
A Transformer-based Framework for Multivariate Time Series Representation LearningCode1
Self-training Improves Pre-training for Natural Language UnderstandingCode1
Unsupervised Pre-training for Biomedical Question Answering—0
ERNIE at SemEval-2020 Task 10: Learning Word Emphasis Selection by Pre-trained Language Model—0
m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural NetworksCode0
Unsupervised Learning For Sequence-to-sequence Text-to-speech For Low-resource Languages—0
Spatiotemporal Contrastive Video Representation LearningCode1
Functional Regularization for Representation Learning: A Unified Theoretical PerspectiveCode0
Weakly Supervised Construction of ASR Systems with Massive Video Data—0
SeCo: Exploring Sequence Supervision for Unsupervised Representation LearningCode1
PointContrast: Unsupervised Pre-training for 3D Point Cloud UnderstandingCode1
Unsupervised Deep Representation Learning and Few-Shot Classification of PolSAR Images—0
What Makes for Good Views for Contrastive Learning?—0
A Further Study of Unsupervised Pre-training for Transformer Based Speech RecognitionCode1
Measles Rash Identification Using Residual Deep Convolutional Neural Network—0
Rolling-Unrolling LSTMs for Action Anticipation from First-Person VideoCode1
TACRED Revisited: A Thorough Evaluation of the TACRED Relation Extraction TaskCode1
Lottery Hypothesis based Unsupervised Pre-training for Model Compression in Federated Learning—0
Pre-training Text Representations as Meta Learning—0
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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