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 2851–2900 of 6661 papers

TitleStatusHype
Knowledge-aware Dual-side Attribute-enhanced RecommendationCode0
Contextualized Spatio-Temporal Contrastive Learning with Self-SupervisionCode0
JTCSE: Joint Tensor-Modulus Constraints and Cross-Attention for Unsupervised Contrastive Learning of Sentence EmbeddingsCode0
Contextuality Helps Representation Learning for Generalized Category DiscoveryCode0
Balanced Adversarial Training: Balancing Tradeoffs between Fickleness and Obstinacy in NLP ModelsCode0
Enhancing Homophily-Heterophily Separation: Relation-Aware Learning in Heterogeneous GraphsCode0
PSP: Pre-Training and Structure Prompt Tuning for Graph Neural NetworksCode0
JojoSCL: Shrinkage Contrastive Learning for single-cell RNA sequence ClusteringCode0
Enhancing Graph Contrastive Learning with Reliable and Informative Augmentation for RecommendationCode0
Reducing Predictive Feature Suppression in Resource-Constrained Contrastive Image-Caption RetrievalCode0
Label Structure Preserving Contrastive Embedding for Multi-Label Learning with Missing LabelsCode0
Joint Masked Reconstruction and Contrastive Learning for Mining Interactions Between ProteinsCode0
Cross-Model Cross-Stream Learning for Self-Supervised Human Action RecognitionCode0
Beyond Random Augmentations: Pretraining with Hard ViewsCode0
Harmony: A Joint Self-Supervised and Weakly-Supervised Framework for Learning General Purpose Visual RepresentationsCode0
Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate RainsCode0
JIGMARK: A Black-Box Approach for Enhancing Image Watermarks against Diffusion Model EditsCode0
Topology Only Pre-Training: Towards Generalised Multi-Domain Graph ModelsCode0
Bundle Recommendation with Item-level Causation-enhanced Multi-view LearningCode0
Pseudolabel guided pixels contrast for domain adaptive semantic segmentationCode0
IRConStyle: Image Restoration Framework Using Contrastive Learning and Style TransferCode0
Enhancing Contrastive Learning Inspired by the Philosophy of "The Blind Men and the Elephant"Code0
Adaptive Hypergraph Network for Trust PredictionCode0
Enhancing Contrastive Learning-based Electrocardiogram Pretrained Model with Patient Memory QueueCode0
HaSa: Hardness and Structure-Aware Contrastive Knowledge Graph EmbeddingCode0
IPCL: Iterative Pseudo-Supervised Contrastive Learning to Improve Self-Supervised Feature RepresentationCode0
JCSE: Contrastive Learning of Japanese Sentence Embeddings and Its ApplicationsCode0
Joint Prediction of Meningioma Grade and Brain Invasion via Task-Aware Contrastive LearningCode0
Intra-video Positive Pairs in Self-Supervised Learning for UltrasoundCode0
Enhancing Cardiovascular Disease Prediction through Multi-Modal Self-Supervised LearningCode0
Enhancing Audio-Language Models through Self-Supervised Post-Training with Text-Audio PairsCode0
Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited PlacesCode0
Intra- and Inter-modal Context Interaction Modeling for Conversational Speech SynthesisCode0
Intrinsic and Extrinsic Factor Disentanglement for Recommendation in Various Context ScenariosCode0
Adaptive H&E-IHC information fusion staining framework based on feature extraCode0
Interventional Video Grounding with Dual Contrastive LearningCode0
Intermediate Domain-guided Adaptation for Unsupervised Chorioallantoic Membrane Vessel SegmentationCode0
Backdoor Attack on Unpaired Medical Image-Text Foundation Models: A Pilot Study on MedCLIPCode0
Interactive Dimensionality Reduction for Comparative AnalysisCode0
Enhanced Long-Tailed Recognition with Contrastive CutMix AugmentationCode0
Joint Representation Learning for Text and 3D Point CloudCode0
ENGAGE: Explanation Guided Data Augmentation for Graph Representation LearningCode0
Self-supervised Multi-modal Training from Uncurated Image and Reports Enables Zero-shot Oversight Artificial Intelligence in RadiologyCode0
End-to-End Supervised Multilabel Contrastive LearningCode0
Constructing Contrastive samples via Summarization for Text Classification with limited annotationsCode0
Instance Smoothed Contrastive Learning for Unsupervised Sentence EmbeddingCode0
Integrating Contrastive Learning with Dynamic Models for Reinforcement Learning from ImagesCode0
Encoding Hierarchical Schema via Concept Flow for Multifaceted Ideology DetectionCode0
A Vlogger-augmented Graph Neural Network Model for Micro-video RecommendationCode0
In-sample Contrastive Learning and Consistent Attention for Weakly Supervised Object LocalizationCode0
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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