SOTAVerified

Contrastive Learning

Contrastive Learning is a deep learning technique for unsupervised representation learning. The goal is to learn a representation of data such that similar instances are close together in the representation space, while dissimilar instances are far apart.

It has been shown to be effective in various computer vision and natural language processing tasks, including image retrieval, zero-shot learning, and cross-modal retrieval. In these tasks, the learned representations can be used as features for downstream tasks such as classification and clustering.

(Image credit: Schroff et al. 2015)

Papers

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Showing 1501–1550 of 6661 papers

TitleStatusHype
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation LearningCode1
3D Infomax improves GNNs for Molecular Property PredictionCode1
Phone-to-audio alignment without text: A Semi-supervised ApproachCode1
Learning 3D Representations of Molecular Chirality with Invariance to Bond RotationsCode1
Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot FillingCode1
Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source DataCode1
The Information Geometry of Unsupervised Reinforcement LearningCode1
KNN-BERT: Fine-Tuning Pre-Trained Models with KNN ClassifierCode1
ProGCL: Rethinking Hard Negative Mining in Graph Contrastive LearningCode1
Consistent Explanations by Contrastive LearningCode1
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial LearningCode1
Motion-aware Contrastive Video Representation Learning via Foreground-background MergingCode1
Contrastive Label Disambiguation for Partial Label LearningCode1
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillationsCode1
Compressive Visual RepresentationsCode1
DialogueCSE: Dialogue-based Contrastive Learning of Sentence EmbeddingsCode1
Hard-sample Guided Hybrid Contrast Learning for Unsupervised Person Re-IdentificationCode1
Weakly Supervised Contrastive Learning for Chest X-Ray Report GenerationCode1
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property PredictionCode1
DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style EditingCode1
AutoGCL: Automated Graph Contrastive Learning via Learnable View GeneratorsCode1
On the Importance of Distractors for Few-Shot ClassificationCode1
MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language ModelsCode1
Pointly-supervised 3D Scene Parsing with Viewpoint BottleneckCode1
Self-supervised Contrastive Learning for EEG-based Sleep StagingCode1
Semi-supervised Contrastive Learning for Label-efficient Medical Image SegmentationCode1
CONTaiNER: Few-Shot Named Entity Recognition via Contrastive LearningCode1
SupCL-Seq: Supervised Contrastive Learning for Downstream Optimized Sequence RepresentationsCode1
Few-Shot Intent Detection via Contrastive Pre-Training and Fine-TuningCode1
Pairwise Supervised Contrastive Learning of Sentence RepresentationsCode1
Exploring Task Difficulty for Few-Shot Relation ExtractionCode1
Contrastive Quantization with Code Memory for Unsupervised Image RetrievalCode1
Topic-Aware Contrastive Learning for Abstractive Dialogue SummarizationCode1
Efficient Contrastive Learning via Novel Data Augmentation and Curriculum LearningCode1
TACS: Taxonomy Adaptive Cross-Domain Semantic SegmentationCode1
ESimCSE: Enhanced Sample Building Method for Contrastive Learning of Unsupervised Sentence EmbeddingCode1
Preservational Learning Improves Self-supervised Medical Image Models by Reconstructing Diverse ContextsCode1
Smoothed Contrastive Learning for Unsupervised Sentence EmbeddingCode1
Sequence Level Contrastive Learning for Text SummarizationCode1
Supervised Contrastive Learning for Multimodal Unreliable News Detection in COVID-19 PandemicCode1
Contrastive Representation Learning for Exemplar-Guided Paraphrase GenerationCode1
Self-supervised Pseudo Multi-class Pre-training for Unsupervised Anomaly Detection and Segmentation in Medical ImagesCode1
Imposing Relation Structure in Language-Model Embeddings Using Contrastive LearningCode1
Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential RecommendationCode1
ReMeDi: Resources for Multi-domain, Multi-service, Medical DialoguesCode1
Multi-Sample based Contrastive Loss for Top-k RecommendationCode1
ScatSimCLR: self-supervised contrastive learning with pretext task regularization for small-scale datasetsCode1
When Do Contrastive Learning Signals Help Spatio-Temporal Graph Forecasting?Code1
Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text SummarizationCode1
Alleviating Exposure Bias via Contrastive Learning for Abstractive Text SummarizationCode1
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All datasetsimagenet-1k10,000 People - Human Pose Recognition DataCIFAR-10STL-10

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ResNet50ImageNet Top-1 Accuracy73.6—Unverified
2ResNet50ImageNet Top-1 Accuracy73—Unverified
3ResNet50ImageNet Top-1 Accuracy71.1—Unverified
4ResNet50ImageNet Top-1 Accuracy69.3—Unverified
5ResNet50 (v2)ImageNet Top-1 Accuracy67.6—Unverified
6ResNet50 (v2)ImageNet Top-1 Accuracy63.8—Unverified
7ResNet50ImageNet Top-1 Accuracy63.6—Unverified
8ResNet50ImageNet Top-1 Accuracy61.5—Unverified
9ResNet50ImageNet Top-1 Accuracy61.5—Unverified
10ResNet50 (4×)ImageNet Top-1 Accuracy61.3—Unverified
#ModelMetricClaimedVerifiedStatus
110..5sec1—Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)84.77—Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)85.55—Unverified