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 4076–4100 of 6661 papers

Title	Date	Tasks	Status	Hype
Similarity Contrastive Estimation for Image and Video Soft Contrastive Self-Supervised Learning	Dec 21, 2022	Contrastive LearningLinear evaluation	CodeCode Available	1
CoCo: Coherence-Enhanced Machine-Generated Text Detection Under Data Limitation With Contrastive Learning	Dec 20, 2022	Contrastive LearningText Detection	CodeCode Available	1
Contrastive Learning Reduces Hallucination in Conversations	Dec 20, 2022	Contrastive LearningHallucination	CodeCode Available	1
WACO: Word-Aligned Contrastive Learning for Speech Translation	Dec 19, 2022	Contrastive LearningSpeech-to-Text	CodeCode Available	0
Query-as-context Pre-training for Dense Passage Retrieval	Dec 19, 2022	Contrastive LearningPassage Retrieval	CodeCode Available	1
Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding	Dec 19, 2022	Contrastive Learningdocument understanding	CodeCode Available	0
Disentangling Learnable and Memorizable Data via Contrastive Learning for Semantic Communications	Dec 18, 2022	Contrastive LearningSemantic Communication	—Unverified	0
On Isotropy, Contextualization and Learning Dynamics of Contrastive-based Sentence Representation Learning	Dec 18, 2022	Contrastive LearningRepresentation Learning	CodeCode Available	1
Hyperbolic Hierarchical Contrastive Hashing	Dec 17, 2022	Contrastive LearningRetrieval	—Unverified	0
TCFimt: Temporal Counterfactual Forecasting from Individual Multiple Treatment Perspective	Dec 17, 2022	Contrastive Learningcounterfactual	—Unverified	0
Attentive Mask CLIP	Dec 16, 2022	Contrastive LearningRetrieval	CodeCode Available	1
MAViL: Masked Audio-Video Learners	Dec 15, 2022	Contrastive LearningRetrieval	CodeCode Available	1
NeRF-Art: Text-Driven Neural Radiance Fields Stylization	Dec 15, 2022	Contrastive LearningNeRF	CodeCode Available	1
CLIPPO: Image-and-Language Understanding from Pixels Only	Dec 15, 2022	Contrastive Learningimage-classification	—Unverified	0
Establishing a stronger baseline for lightweight contrastive models	Dec 14, 2022	Contrastive LearningLinear evaluation	CodeCode Available	0
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning	Dec 14, 2022	Contrastive LearningData Augmentation	CodeCode Available	1
Significantly improving zero-shot X-ray pathology classification via fine-tuning pre-trained image-text encoders	Dec 14, 2022	ClassificationContrastive Learning	—Unverified	0
Understanding Zero-Shot Adversarial Robustness for Large-Scale Models	Dec 14, 2022	Adversarial RobustnessContrastive Learning	CodeCode Available	1
Mitigating Negative Style Transfer in Hybrid Dialogue System	Dec 14, 2022	Contrastive LearningStyle Transfer	CodeCode Available	0
Tailoring Visual Object Representations to Human Requirements: A Case Study with a Recycling Robot	Dec 14, 2022	Contrastive LearningObject	CodeCode Available	0
Generative artificial intelligence-enabled dynamic detection of nicotine-related circuits	Dec 13, 2022	Contrastive Learning	—Unverified	0
A Machine Learning Enhanced Approach for Automated Sunquake Detection in Acoustic Emission Maps	Dec 13, 2022	Contrastive LearningData Augmentation	—Unverified	0
Boosting Semi-Supervised Learning with Contrastive Complementary Labeling	Dec 13, 2022	Contrastive Learning	—Unverified	0
On the Evolution of (Hateful) Memes by Means of Multimodal Contrastive Learning	Dec 13, 2022	Contrastive Learning	CodeCode Available	1
Coarse-to-Fine Contrastive Learning on Graphs	Dec 13, 2022	Contrastive LearningLearning-To-Rank	—Unverified	0

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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