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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 1126–1150 of 6661 papers

Title	Date	Tasks	Status	Hype	Score
Contrastive Learning of Musical Representations	Mar 17, 2021	Contrastive LearningLinear evaluation	CodeCode Available	1	5
Contrastive Learning of User Behavior Sequence for Context-Aware Document Ranking	Aug 24, 2021	Contrastive LearningData Augmentation	CodeCode Available	1	5
Contrastive Learning with Bidirectional Transformers for Sequential Recommendation	Aug 8, 2022	Contrastive LearningSequential Recommendation	CodeCode Available	1	5
Contrastive Label Disambiguation for Partial Label Learning	Sep 29, 2021	Contrastive LearningPartial Label Learning	CodeCode Available	1	5
Graph Masked Autoencoder for Sequential Recommendation	May 8, 2023	Contrastive LearningData Augmentation	CodeCode Available	1	5
A Message Passing Perspective on Learning Dynamics of Contrastive Learning	Mar 8, 2023	Contrastive LearningGraph Attention	CodeCode Available	1	5
Contrastive Learning Reduces Hallucination in Conversations	Dec 20, 2022	Contrastive LearningHallucination	CodeCode Available	1	5
From t-SNE to UMAP with contrastive learning	Jun 3, 2022	Contrastive LearningRepresentation Learning	CodeCode Available	1	5
Generalized Category Discovery with Large Language Models in the Loop	Dec 18, 2023	Active LearningContrastive Learning	CodeCode Available	1	5
Contrastive Learning with Cross-Modal Knowledge Mining for Multimodal Human Activity Recognition	May 20, 2022	Activity RecognitionContrastive Learning	CodeCode Available	1	5
Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition	Oct 8, 2024	Contrastive LearningDensity Estimation	CodeCode Available	1	5
Continuous Learning for Android Malware Detection	Feb 8, 2023	Active LearningAndroid Malware Detection	CodeCode Available	1	5
ContraBAR: Contrastive Bayes-Adaptive Deep RL	Jun 4, 2023	Contrastive LearningMeta Reinforcement Learning	CodeCode Available	1	5
Contrastive Learning with Hard Negative Entities for Entity Set Expansion	Apr 16, 2022	Contrastive LearningLanguage Modeling	CodeCode Available	1	5
ContraCLM: Contrastive Learning For Causal Language Model	Oct 3, 2022	Code GenerationCode Search	CodeCode Available	1	5
BankNote-Net: Open dataset for assistive universal currency recognition	Apr 7, 2022	Contrastive LearningFew-Shot Learning	CodeCode Available	1	5
Contrastive Learning with Hard Negative Samples	Oct 9, 2020	Contrastive LearningMetric Learning	CodeCode Available	1	5
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond	Mar 12, 2023	Contrastive Learning	CodeCode Available	1	5
ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing	Dec 18, 2023	Contrastive Learningde novo peptide sequencing	CodeCode Available	1	5
BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis	Oct 31, 2023	Contrastive LearningSelf-Supervised Learning	CodeCode Available	1	5
Contrastive Learning with Stronger Augmentations	Apr 15, 2021	Contrastive LearningRepresentation Learning	CodeCode Available	1	5
Generating and Weighting Semantically Consistent Sample Pairs for Ultrasound Contrastive Learning	Dec 8, 2022	Cancer ClassificationContrastive Learning	CodeCode Available	1	5
Contrastive Masked Autoencoders are Stronger Vision Learners	Jul 27, 2022	Contrastive LearningDecoder	CodeCode Available	1	5
Contrast and Classify: Training Robust VQA Models	Oct 13, 2020	Contrastive LearningData Augmentation	CodeCode Available	1	5
Graph Contrastive Learning for Anomaly Detection	Aug 17, 2021	Anomaly DetectionBinary Classification	CodeCode Available	1	5

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All datasets imagenet-1k 10,000 People - Human Pose Recognition Data CIFAR-10 STL-10

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ResNet50	ImageNet Top-1 Accuracy	73.6	—	Unverified
2	ResNet50	ImageNet Top-1 Accuracy	73	—	Unverified
3	ResNet50	ImageNet Top-1 Accuracy	71.1	—	Unverified
4	ResNet50	ImageNet Top-1 Accuracy	69.3	—	Unverified
5	ResNet50 (v2)	ImageNet Top-1 Accuracy	67.6	—	Unverified
6	ResNet50 (v2)	ImageNet Top-1 Accuracy	63.8	—	Unverified
7	ResNet50	ImageNet Top-1 Accuracy	63.6	—	Unverified
8	ResNet50	ImageNet Top-1 Accuracy	61.5	—	Unverified
9	ResNet50	ImageNet Top-1 Accuracy	61.5	—	Unverified
10	ResNet50 (4×)	ImageNet Top-1 Accuracy	61.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	1	0..5sec	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IPCL (ResNet18)	Accuracy (Top-1)	84.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IPCL (ResNet18)	Accuracy (Top-1)	85.55	—	Unverified