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 201–225 of 265 papers

TitleStatusHype
On Architectures and Training for Raw Waveform Feature Extraction in ASR—0
Foundation Model for Wireless Technology Recognition Using IQ Timeseries—0
GFlowNet Pretraining with Inexpensive Rewards—0
GiBERT: Introducing Linguistic Knowledge into BERT through a Lightweight Gated Injection Method—0
HindiLLM: Large Language Model for Hindi—0
Improving Abstractive Dialogue Summarization with Hierarchical Pretraining and Topic Segment—0
Improving On-Screen Sound Separation for Open-Domain Videos with Audio-Visual Self-Attention—0
Incomplete Multi-View Multi-label Learning via Disentangled Representation and Label Semantic Embedding—0
Incorporating Unlabelled Data into Bayesian Neural Networks—0
Is MixIT Really Unsuitable for Correlated Sources? Exploring MixIT for Unsupervised Pre-training in Music Source Separation—0
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
Maximal Multiverse Learning for Promoting Cross-Task Generalization of Fine-Tuned Language Models—0
Measles Rash Identification Using Residual Deep Convolutional Neural Network—0
MLIP: Enhancing Medical Visual Representation with Divergence Encoder and Knowledge-guided Contrastive Learning—0
Multi-Modal Unsupervised Pre-Training for Surgical Operating Room Workflow Analysis—0
Multi-Stage Multi-Modal Pre-Training for Automatic Speech 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