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 3701–3750 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
CLCE: An Approach to Refining Cross-Entropy and Contrastive Learning for Optimized Learning Fusion—0
Contrastive Learning of Shared Spatiotemporal EEG Representations Across Individuals for Naturalistic Neuroscience—0
Self-supervised Visualisation of Medical Image DatasetsCode0
Overcoming Dimensional Collapse in Self-supervised Contrastive Learning for Medical Image SegmentationCode0
Noise-BERT: A Unified Perturbation-Robust Framework with Noise Alignment Pre-training for Noisy Slot Filling Task—0
The Effectiveness of Graph Contrastive Learning on Mathematical Information RetrievalCode0
Multi-organ Self-supervised Contrastive Learning for Breast Lesion Segmentation—0
Unsupervised learning based object detection using Contrastive Learning—0
Event-aware Video Corpus Moment Retrieval—0
CCFC++: Enhancing Federated Clustering through Feature Decorrelation—0
MoELoRA: Contrastive Learning Guided Mixture of Experts on Parameter-Efficient Fine-Tuning for Large Language Models—0
Analysis of Using Sigmoid Loss for Contrastive Learning—0
Revealing the Relationship Between Publication Bias and Chemical Reactivity with Contrastive Learning—0
HU at SemEval-2024 Task 8A: Can Contrastive Learning Learn Embeddings to Detect Machine-Generated Text?Code0
Separating common from salient patterns with Contrastive Representation LearningCode0
Leveraging Contrastive Learning for Few-shot Geolocation of Social Posts—0
Attacks on Node Attributes in Graph Neural NetworksCode0
Adversarial Feature Alignment: Balancing Robustness and Accuracy in Deep Learning via Adversarial Training—0
Language-guided Image Reflection Separation—0
PASCL: Supervised Contrastive Learning with Perturbative Augmentation for Particle Decay ReconstructionCode0
A Temporally Disentangled Contrastive Diffusion Model for Spatiotemporal Imputation—0
Assessing News Thumbnail Representativeness: Counterfactual text can enhance the cross-modal matching abilityCode0
Dynamic Patch-aware Enrichment Transformer for Occluded Person Re-Identification—0
A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Models—0
Pretext Training Algorithms for Event Sequence Data—0
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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