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

Showing 28262850 of 6661 papers

TitleStatusHype
HierarchicalContrast: A Coarse-to-Fine Contrastive Learning Framework for Cross-Domain Zero-Shot Slot FillingCode0
EHI: End-to-end Learning of Hierarchical Index for Efficient Dense Retrieval0
CLExtract: Recovering Highly Corrupted DVB/GSE Satellite Stream with Contrastive Learning0
Incorporating Domain Knowledge Graph into Multimodal Movie Genre Classification with Self-Supervised Attention and Contrastive LearningCode0
Hyp-UML: Hyperbolic Image Retrieval with Uncertainty-aware Metric Learning0
Enhancing Text-based Knowledge Graph Completion with Zero-Shot Large Language Models: A Focus on Semantic EnhancementCode1
SimCKP: Simple Contrastive Learning of Keyphrase RepresentationsCode1
X-Pose: Detecting Any KeypointsCode2
Rethinking Negative Pairs in Code SearchCode1
Splicing Up Your Predictions with RNA Contrastive LearningCode0
Visual Self-supervised Learning Scheme for Dense Prediction Tasks on X-ray Images0
Language Models As Semantic IndexersCode1
Heuristic Vision Pre-Training with Self-Supervised and Supervised Multi-Task Learning0
IMITATE: Clinical Prior Guided Hierarchical Vision-Language Pre-trainingCode0
The Solution for the CVPR2023 NICE Image Captioning Challenge0
Improving Contrastive Learning of Sentence Embeddings with Focal-InfoNCECode0
DrugCLIP: Contrastive Protein-Molecule Representation Learning for Virtual ScreeningCode1
Contrastive Prompt Learning-based Code Search based on Interaction Matrix0
InfoCL: Alleviating Catastrophic Forgetting in Continual Text Classification from An Information Theoretic PerspectiveCode1
A Novel Contrastive Learning Method for Clickbait Detection on RoCliCo: A Romanian Clickbait Corpus of News ArticlesCode0
Antenna Response Consistency Driven Self-supervised Learning for WIFI-based Human Activity Recognition0
Topic-DPR: Topic-based Prompts for Dense Passage Retrieval0
Aligning Language Models with Human Preferences via a Bayesian ApproachCode1
WeatherDepth: Curriculum Contrastive Learning for Self-Supervised Depth Estimation under Adverse Weather ConditionsCode1
C^2M-DoT: Cross-modal consistent multi-view medical report generation with domain transfer network0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ResNet50ImageNet Top-1 Accuracy73.6Unverified
2ResNet50ImageNet Top-1 Accuracy73Unverified
3ResNet50ImageNet Top-1 Accuracy71.1Unverified
4ResNet50ImageNet Top-1 Accuracy69.3Unverified
5ResNet50 (v2)ImageNet Top-1 Accuracy67.6Unverified
6ResNet50 (v2)ImageNet Top-1 Accuracy63.8Unverified
7ResNet50ImageNet Top-1 Accuracy63.6Unverified
8ResNet50ImageNet Top-1 Accuracy61.5Unverified
9ResNet50ImageNet Top-1 Accuracy61.5Unverified
10ResNet50 (4×)ImageNet Top-1 Accuracy61.3Unverified
#ModelMetricClaimedVerifiedStatus
110..5sec1Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)84.77Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)85.55Unverified