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 2301–2325 of 6661 papers

Title	Date	Tasks	Status	Score
MarsEclipse at SemEval-2023 Task 3: Multi-Lingual and Multi-Label Framing Detection with Contrastive Learning	Apr 20, 2023	Contrastive Learning	CodeCode Available	5
Adversarial Learning Data Augmentation for Graph Contrastive Learning in Recommendation	Feb 5, 2023	Contrastive LearningData Augmentation	CodeCode Available	5
Caption Feature Space Regularization for Audio Captioning	Apr 18, 2022	Audio captioningContrastive Learning	CodeCode Available	5
Mao-Zedong At SemEval-2023 Task 4: Label Represention Multi-Head Attention Model With Contrastive Learning-Enhanced Nearest Neighbor Mechanism For Multi-Label Text Classification	Jul 11, 2023	Contrastive LearningMulti Label Text Classification	CodeCode Available	5
Manifold Contrastive Learning with Variational Lie Group Operators	Jun 23, 2023	Contrastive LearningRepresentation Learning	CodeCode Available	5
Adversarial Graph Contrastive Learning with Information Regularization	Feb 14, 2022	Contrastive LearningData Augmentation	CodeCode Available	5
Making Pre-trained Language Models Better Continual Few-Shot Relation Extractors	Feb 24, 2024	Contrastive LearningPrompt Learning	CodeCode Available	5
Making Pre-trained Language Models End-to-end Few-shot Learners with Contrastive Prompt Tuning	Apr 1, 2022	Contrastive Learning	CodeCode Available	5
Contrastive Visual-Linguistic Pretraining	Jul 26, 2020	Contrastive Learningregression	CodeCode Available	5
Making the Most of Text Semantics to Improve Biomedical Vision--Language Processing	Apr 21, 2022	Contrastive LearningLanguage Modeling	CodeCode Available	5
ManiNeg: Manifestation-guided Multimodal Pretraining for Mammography Classification	Sep 24, 2024	ClassificationContrastive Learning	CodeCode Available	5
MA-AVT: Modality Alignment for Parameter-Efficient Audio-Visual Transformers	Jun 7, 2024	audio-visual learningContrastive Learning	CodeCode Available	5
Single-Pass Contrastive Learning Can Work for Both Homophilic and Heterophilic Graph	Nov 20, 2022	Contrastive Learning	CodeCode Available	5
Can Self-Supervised Representation Learning Methods Withstand Distribution Shifts and Corruptions?	Jul 31, 2023	Contrastive LearningKnowledge Distillation	CodeCode Available	5
M3ANet: Multi-scale and Multi-Modal Alignment Network for Brain-Assisted Target Speaker Extraction	May 31, 2025	Contrastive LearningEEG	CodeCode Available	5
Contrastive Variational Autoencoder Enhances Salient Features	Feb 12, 2019	Contrastive Learning	CodeCode Available	5
UoR-NCL at SemEval-2025 Task 1: Using Generative LLMs and CLIP Models for Multilingual Multimodal Idiomaticity Representation	Feb 28, 2025	Contrastive LearningData Augmentation	CodeCode Available	5
Machine Unlearning in Hyperbolic vs. Euclidean Multimodal Contrastive Learning: Adapting Alignment Calibration to MERU	Mar 19, 2025	Contrastive LearningMachine Unlearning	CodeCode Available	5
Can Machines Resonate with Humans? Evaluating the Emotional and Empathic Comprehension of LMs	Jun 17, 2024	Contrastive Learning	CodeCode Available	5
Contrastive Transformer Learning with Proximity Data Generation for Text-Based Person Search	Nov 15, 2023	Contrastive LearningCross-Modal Retrieval	CodeCode Available	5
A Contrastive Learning Scheme with Transformer Innate Patches	Mar 26, 2023	Contrastive Learningimage-classification	CodeCode Available	5
Contrastive Training of Complex-Valued Autoencoders for Object Discovery	May 24, 2023	Contrastive LearningObject	CodeCode Available	5
Approximate Bijective Correspondence for isolating factors of variation	Sep 29, 2021	Contrastive LearningData Augmentation	CodeCode Available	5
M3: A Multi-Task Mixed-Objective Learning Framework for Open-Domain Multi-Hop Dense Sentence Retrieval	Mar 21, 2024	Contrastive LearningFact Verification	CodeCode Available	5
Looking Beyond Corners: Contrastive Learning of Visual Representations for Keypoint Detection and Description Extraction	Dec 22, 2021	Contrastive LearningKeypoint Detection	CodeCode Available	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