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 3701–3725 of 6661 papers

TitleStatusHype
Leveraging Diverse Modeling Contexts with Collaborating Learning for Neural Machine Translation—0
Classes Are Not Equal: An Empirical Study on Image Recognition Fairness—0
LocalGCL: Local-aware Contrastive Learning for Graphs—0
Analyzing Regional Organization of the Human Hippocampus in 3D-PLI Using Contrastive Learning and Geometric Unfolding—0
FaultProfIT: Hierarchical Fault Profiling of Incident Tickets in Large-scale Cloud Systems—0
Demonstrating and Reducing Shortcuts in Vision-Language Representation LearningCode0
High-Frequency-aware Hierarchical Contrastive Selective Coding for Representation Learning on Text-attributed Graphs—0
Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings—0
COMAE: COMprehensive Attribute Exploration for Zero-shot Hashing—0
Deep Contrastive Graph Learning with Clustering-Oriented Guidance—0
FGBERT: Function-Driven Pre-trained Gene Language Model for Metagenomics—0
Explainable Contrastive and Cost-Sensitive Learning for Cervical Cancer ClassificationCode0
Making Pre-trained Language Models Better Continual Few-Shot Relation ExtractorsCode0
CLIPose: Category-Level Object Pose Estimation with Pre-trained Vision-Language Knowledge—0
Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks—0
IRConStyle: Image Restoration Framework Using Contrastive Learning and Style TransferCode0
Debiased Model-based Interactive Recommendation—0
Smoothed Graph Contrastive Learning via Seamless Proximity IntegrationCode0
GS-EMA: Integrating Gradient Surgery Exponential Moving Average with Boundary-Aware Contrastive Learning for Enhanced Domain Generalization in Aneurysm SegmentationCode0
Cohere3D: Exploiting Temporal Coherence for Unsupervised Representation Learning of Vision-based Autonomous Driving—0
Unsupervised Domain Adaptation for Brain Vessel Segmentation through Transwarp Contrastive LearningCode0
Entity-level Factual Adaptiveness of Fine-tuning based Abstractive Summarization Models—0
CI w/o TN: Context Injection without Task Name for Procedure Planning—0
Self-Adaptive Reconstruction with Contrastive Learning for Unsupervised Sentence Embeddings—0
Addressing Order Sensitivity of In-Context Demonstration Examples in Causal Language ModelsCode0
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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