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 401–450 of 6661 papers

TitleStatusHype
ContraCLM: Contrastive Learning For Causal Language ModelCode1
A Self-Supervised Gait Encoding Approach with Locality-Awareness for 3D Skeleton Based Person Re-IdentificationCode1
A Contrastive Cross-Channel Data Augmentation Framework for Aspect-based Sentiment AnalysisCode1
A Self-supervised Method for Entity AlignmentCode1
Contrastive Learning Reduces Hallucination in ConversationsCode1
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive LearningCode1
Contrastive Learning with Boosted MemorizationCode1
Contrastive Learning with Continuous Proxy Meta-Data for 3D MRI ClassificationCode1
Contrastive Learning with Hard Negative Entities for Entity Set ExpansionCode1
A Sentence is Worth 128 Pseudo Tokens: A Semantic-Aware Contrastive Learning Framework for Sentence EmbeddingsCode1
Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical ReasoningCode1
Contrastive Learning with Stronger AugmentationsCode1
A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect DetectionCode1
Contrastive Masked Autoencoders are Stronger Vision LearnersCode1
Continuous Contrastive Learning for Long-Tailed Semi-Supervised RecognitionCode1
A Simple Contrastive Learning Objective for Alleviating Neural Text DegenerationCode1
A simple, efficient and scalable contrastive masked autoencoder for learning visual representationsCode1
Continuous Learning for Android Malware DetectionCode1
Contrastive Neural Processes for Self-Supervised LearningCode1
Contrastive Object-level Pre-training with Spatial Noise Curriculum LearningCode1
A Simple Graph Contrastive Learning Framework for Short Text ClassificationCode1
A Simple Long-Tailed Recognition Baseline via Vision-Language ModelCode1
Learning the Unlearned: Mitigating Feature Suppression in Contrastive LearningCode1
A Simple yet Effective Relation Information Guided Approach for Few-Shot Relation ExtractionCode1
Contrastive Registration for Unsupervised Medical Image SegmentationCode1
Contrastive Representation DistillationCode1
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and BeyondCode1
Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RLCode1
Contrastive Self-supervised Sequential Recommendation with Robust AugmentationCode1
Contrastive Semi-supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical StructuresCode1
Contrastive Tuning: A Little Help to Make Masked Autoencoders ForgetCode1
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement LearningCode1
Assisting Mathematical Formalization with A Learning-based Premise RetrieverCode1
Contrastive Video Question Answering via Video Graph TransformerCode1
ContrastNet: A Contrastive Learning Framework for Few-Shot Text ClassificationCode1
AstroCLIP: A Cross-Modal Foundation Model for GalaxiesCode1
Contrast, Stylize and Adapt: Unsupervised Contrastive Learning Framework for Domain Adaptive Semantic SegmentationCode1
Contrast then Memorize: Semantic Neighbor Retrieval-Enhanced Inductive Multimodal Knowledge Graph CompletionCode1
A Supervised Information Enhanced Multi-Granularity Contrastive Learning Framework for EEG Based Emotion RecognitionCode1
COPNER: Contrastive Learning with Prompt Guiding for Few-shot Named Entity RecognitionCode1
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural NetworksCode1
Correspondence Matters for Video Referring Expression ComprehensionCode1
A graph-transformer for whole slide image classificationCode1
CoSQA: 20,000+ Web Queries for Code Search and Question AnsweringCode1
ContrastCAD: Contrastive Learning-based Representation Learning for Computer-Aided Design ModelsCode1
CoT-BERT: Enhancing Unsupervised Sentence Representation through Chain-of-ThoughtCode1
A Hierarchical Dual Model of Environment- and Place-Specific Utility for Visual Place RecognitionCode1
Contrastive Deep Nonnegative Matrix Factorization for Community DetectionCode1
cRedAnno+: Annotation Exploitation in Self-Explanatory Lung Nodule DiagnosisCode1
Contrastive Learning for Neural Topic ModelCode1
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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