SOTAVerified

Unsupervised Pre-training

Pre-training a neural network using unsupervised (self-supervised) auxiliary tasks on unlabeled data.

Papers

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Showing 151–200 of 265 papers

TitleStatusHype
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
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
Pre-training Text Representations as Meta Learning—0
Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models—0
Range-aware Positional Encoding via High-order Pretraining: Theory and Practice—0
Recognizing UMLS Semantic Types with Deep Learning—0
Representation Learning for Weakly Supervised Relation Extraction—0
Research on CPI Prediction Based on Natural Language Processing—0
Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images—0
Risk Assessment Framework for Code LLMs via Leveraging Internal States—0
R-LAtte: Attention Module for Visual Control via Reinforcement Learning—0
Self-FuseNet: Data Free Unsupervised Remote Sensing Image Super-Resolution—0
Self-Supervised Relative Depth Learning for Urban Scene Understanding—0
Semi-supervised Facial Action Unit Intensity Estimation with Contrastive Learning—0
Semi-Supervised Semantic Segmentation of Cell Nuclei via Diffusion-based Large-Scale Pre-Training and Collaborative Learning—0
SLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training—0
SMiRL: Surprise Minimizing RL in Entropic Environments—0
Spiral Contrastive Learning: An Efficient 3D Representation Learning Method for Unannotated CT Lesions—0
SYNFIX: Automatically Fixing Syntax Errors using Compiler Diagnostics—0
Synthetic vascular structure generation for unsupervised pre-training in CTA segmentation tasks—0
Targeted Forgetting of Image Subgroups in CLIP Models—0
Temporal Autoencoding Improves Generative Models of Time Series—0
Temporal Interpolation as an Unsupervised Pretraining Task for Optical Flow Estimation—0
The Efficiency of Pre-training with Objective Masking in Pseudo Labeling for Semi-Supervised Text Classification—0
Towards General Text Embeddings with Multi-stage Contrastive Learning—0
TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Training—0
Transfer Learning for Context-Aware Spoken Language Understanding—0
Transferring self-supervised pre-trained models for SHM data anomaly detection with scarce labeled data—0
Triplet Contrastive Learning for Brain Tumor Classification—0
UHH-LT at SemEval-2019 Task 6: Supervised vs. Unsupervised Transfer Learning for Offensive Language Detection—0
Understanding Semantics from Speech Through Pre-training—0
Unleashing Potential of Unsupervised Pre-Training With Intra-Identity Regularization for Person Re-Identification—0
Unsupervised Active Pre-Training for Reinforcement Learning—0
Unsupervised Deep Feature Extraction for Remote Sensing Image Classification—0
Unsupervised Instance Discriminative Learning for Depression Detection from Speech Signals—0
Unsupervised Learning For Sequence-to-sequence Text-to-speech For Low-resource Languages—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