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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2351–2400 of 6661 papers

TitleStatusHype
MassNet: A Deep Learning Approach for Body Weight Extraction from A Single Pressure ImageCode0
MeDSLIP: Medical Dual-Stream Language-Image Pre-training for Fine-grained AlignmentCode0
Mao-Zedong At SemEval-2023 Task 4: Label Represention Multi-Head Attention Model With Contrastive Learning-Enhanced Nearest Neighbor Mechanism For Multi-Label Text ClassificationCode0
MAPConNet: Self-supervised 3D Pose Transfer with Mesh and Point Contrastive LearningCode0
MAPS: Motivation-Aware Personalized Search via LLM-Driven Consultation AlignmentCode0
Bundle Recommendation with Item-level Causation-enhanced Multi-view LearningCode0
ManiNeg: Manifestation-guided Multimodal Pretraining for Mammography ClassificationCode0
Contrastive Multiple Correspondence Analysis (cMCA): Using Contrastive Learning to Identify Latent Subgroups in Political PartiesCode0
Making Pre-trained Language Models End-to-end Few-shot Learners with Contrastive Prompt TuningCode0
Making the Most of Text Semantics to Improve Biomedical Vision--Language ProcessingCode0
ANOMIX: A Simple yet Effective Hard Negative Generation via Mixing for Graph Anomaly DetectionCode0
Making Pre-trained Language Models Better Continual Few-Shot Relation ExtractorsCode0
COMICS: End-to-end Bi-grained Contrastive Learning for Multi-face Forgery DetectionCode0
Anomaly Multi-classification in Industrial Scenarios: Transferring Few-shot Learning to a New TaskCode0
Contrastive Modules with Temporal Attention for Multi-Task Reinforcement LearningCode0
Manifold Contrastive Learning with Variational Lie Group OperatorsCode0
Bringing Masked Autoencoders Explicit Contrastive Properties for Point Cloud Self-Supervised LearningCode0
Machine Unlearning in Hyperbolic vs. Euclidean Multimodal Contrastive Learning: Adapting Alignment Calibration to MERUCode0
Contrastive Matrix Completion with Denoising and Augmented Graph Views for Robust RecommendationCode0
M3ANet: Multi-scale and Multi-Modal Alignment Network for Brain-Assisted Target Speaker ExtractionCode0
M3: A Multi-Task Mixed-Objective Learning Framework for Open-Domain Multi-Hop Dense Sentence RetrievalCode0
MA-AVT: Modality Alignment for Parameter-Efficient Audio-Visual TransformersCode0
Contrastively Learning Visual Attention as Affordance Cues from Demonstrations for Robotic GraspingCode0
Contrastive Learning with Temporal Correlated Medical Images: A Case Study using Lung Segmentation in Chest X-RaysCode0
Contrastive Learning with Prompt-derived Virtual Semantic Prototypes for Unsupervised Sentence EmbeddingCode0
Low-confidence Samples Matter for Domain AdaptationCode0
Multi-task Pre-training Language Model for Semantic Network CompletionCode0
MarsEclipse at SemEval-2023 Task 3: Multi-Lingual and Multi-Label Framing Detection with Contrastive LearningCode0
Model Editing for LLMs4Code: How Far are We?Code0
Local Aggregation for Unsupervised Learning of Visual EmbeddingsCode0
Low-Contrast-Enhanced Contrastive Learning for Semi-Supervised Endoscopic Image SegmentationCode0
LogiCoL: Logically-Informed Contrastive Learning for Set-based Dense RetrievalCode0
Contrastive Learning with Consistent RepresentationsCode0
Adversarial Bootstrapped Question Representation Learning for Knowledge TracingCode0
Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-trainingCode0
Link Prediction with Non-Contrastive LearningCode0
Lightweight Cross-Lingual Sentence Representation LearningCode0
Lexical Knowledge Internalization for Neural Dialog GenerationCode0
Leveraging Graph Structures to Detect Hallucinations in Large Language ModelsCode0
Advancing Semantic Textual Similarity Modeling: A Regression Framework with Translated ReLU and Smooth K2 LossCode0
Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced RegressionCode0
Leveraging Unlabeled Data for 3D Medical Image Segmentation through Self-Supervised Contrastive LearningCode0
Line Graph Contrastive Learning for Link PredictionCode0
Breccia and basalt classification of thin sections of Apollo rocks with deep learningCode0
Less is More: Multimodal Region Representation via Pairwise Inter-view LearningCode0
Less is More: Selective Reduction of CT Data for Self-Supervised Pre-Training of Deep Learning Models with Contrastive Learning Improves Downstream Classification PerformanceCode0
Leveraging Contrastive Learning and Self-Training for Multimodal Emotion Recognition with Limited Labeled SamplesCode0
Lesion-Aware Contrastive Representation Learning for Histopathology Whole Slide Images AnalysisCode0
Length is a Curse and a Blessing for Document-level SemanticsCode0
An Investigation of Representation and Allocation Harms in Contrastive LearningCode0
Show:102550
← PrevPage 48 of 134Next →
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