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 2451–2475 of 6661 papers

TitleStatusHype
HCL: Improving Graph Representation with Hierarchical Contrastive Learning—0
ChatZero:Zero-shot Cross-Lingual Dialogue Generation via Pseudo-Target Language—0
CheX-Nomaly: Segmenting Lung Abnormalities from Chest Radiographs using Machine Learning—0
HC^2L: Hybrid and Cooperative Contrastive Learning for Cross-lingual Spoken Language Understanding—0
Cross-Modality Learning for Predicting IHC Biomarkers from H&E-Stained Whole-Slide Images—0
A Self-Supervised Learning Pipeline for Demographically Fair Facial Attribute Classification—0
HAVANA: Hard negAtiVe sAmples aware self-supervised coNtrastive leArning for Airborne laser scanning point clouds semantic segmentation—0
HCGR: Hyperbolic Contrastive Graph Representation Learning for Session-based Recommendation—0
HCL-MTC Hierarchical Contrastive Learning for Multi-label Text Classification—0
Cross-modal Contrastive Learning for Speech Translation—0
3D-Consistent Human Avatars with Sparse Inputs via Gaussian Splatting and Contrastive Learning—0
Mastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization—0
HateProof: Are Hateful Meme Detection Systems really Robust?—0
Knowledge-Augmented Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop—0
Chaos is a Ladder: A New Understanding of Contrastive Learning—0
Cross-Modal Attention Consistency for Video-Audio Unsupervised Learning—0
Affinity-Graph-Guided Contractive Learning for Pretext-Free Medical Image Segmentation with Minimal Annotation—0
HateSieve: A Contrastive Learning Framework for Detecting and Segmenting Hateful Content in Multimodal Memes—0
Channel-Wise Contrastive Learning for Learning with Noisy Labels—0
Cross-Lingual Word Alignment for ASEAN Languages with Contrastive Learning—0
A Self-Learning Multimodal Approach for Fake News Detection—0
Cross-Lingual Multi-Hop Knowledge Editing -- Benchmarks, Analysis and a Simple Contrastive Learning based Approach—0
Cross-Lingual IPA Contrastive Learning for Zero-Shot NER—0
A Self-supervised Contrastive Learning Method for Grasp Outcomes Prediction—0
Harvesting Textual and Structured Data from the HAL Publication Repository—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