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 2801–2850 of 6661 papers

TitleStatusHype
LACMA: Language-Aligning Contrastive Learning with Meta-Actions for Embodied Instruction FollowingCode0
Label Refinement via Contrastive Learning for Distantly-Supervised Named Entity RecognitionCode0
Label Structure Preserving Contrastive Embedding for Multi-Label Learning with Missing LabelsCode0
Graph Diffusion Network for Drug-Gene PredictionCode0
Expression Prompt Collaboration Transformer for Universal Referring Video Object SegmentationCode0
Adaptive Multi-head Contrastive LearningCode0
Language Agnostic Multilingual Information Retrieval with Contrastive LearningCode0
L^2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative FilteringCode0
Ensemble Modeling with Contrastive Knowledge Distillation for Sequential RecommendationCode0
BANER: Boundary-Aware LLMs for Few-Shot Named Entity RecognitionCode0
Label-aware Hard Negative Sampling Strategies with Momentum Contrastive Learning for Implicit Hate Speech DetectionCode0
Knowing Where and What: Unified Word Block Pretraining for Document UnderstandingCode0
Knowledge-aware Dual-side Attribute-enhanced RecommendationCode0
Enhancing the Ranking Context of Dense Retrieval Methods through Reciprocal Nearest NeighborsCode0
Keypoint Aware Masked Image ModellingCode0
Balancing Graph Embedding Smoothness in Self-Supervised Learning via Information-Theoretic DecompositionCode0
Key Point Analysis via Contrastive Learning and Extractive Argument SummarizationCode0
JojoSCL: Shrinkage Contrastive Learning for single-cell RNA sequence ClusteringCode0
Balancing Embedding Spectrum for RecommendationCode0
Enhancing Sequential Music Recommendation with Negative Feedback-informed Contrastive LearningCode0
Continual Learning: Less Forgetting, More OOD Generalization via Adaptive Contrastive ReplayCode0
Joint Representation Learning for Text and 3D Point CloudCode0
Joint Searching and Grounding: Multi-Granularity Video Content RetrievalCode0
JTCSE: Joint Tensor-Modulus Constraints and Cross-Attention for Unsupervised Contrastive Learning of Sentence EmbeddingsCode0
Enhancing pretraining efficiency for medical image segmentation via transferability metricsCode0
Adaptive Integration of Partial Label Learning and Negative Learning for Enhanced Noisy Label LearningCode0
Continual Graph Convolutional Network for Text ClassificationCode0
Joint Masked Reconstruction and Contrastive Learning for Mining Interactions Between ProteinsCode0
Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer EnsembleCode0
Balanced Multi-Relational Graph ClusteringCode0
Enhancing Multivariate Time Series-based Solar Flare Prediction with Multifaceted Preprocessing and Contrastive LearningCode0
Enhancing Multimodal Medical Image Classification using Cross-Graph Modal Contrastive LearningCode0
Continual Contrastive Learning for Image ClassificationCode0
Grounding Bodily Awareness in Visual Representations for Efficient Policy LearningCode0
Joint Prediction of Meningioma Grade and Brain Invasion via Task-Aware Contrastive LearningCode0
Cross-Model Cross-Stream Learning for Self-Supervised Human Action RecognitionCode0
AmCLR: Unified Augmented Learning for Cross-Modal RepresentationsCode0
Enhancing Micro Gesture Recognition for Emotion Understanding via Context-aware Visual-Text Contrastive LearningCode0
JCSE: Contrastive Learning of Japanese Sentence Embeddings and Its ApplicationsCode0
Enhancing Item-level Bundle Representation for Bundle RecommendationCode0
JIGMARK: A Black-Box Approach for Enhancing Image Watermarks against Diffusion Model EditsCode0
Contextualized Spatio-Temporal Contrastive Learning with Self-SupervisionCode0
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
IPCL: Iterative Pseudo-Supervised Contrastive Learning to Improve Self-Supervised Feature RepresentationCode0
Enhancing Graph Contrastive Learning with Reliable and Informative Augmentation for RecommendationCode0
IRConStyle: Image Restoration Framework Using Contrastive Learning and Style TransferCode0
Topology Only Pre-Training: Towards Generalised Multi-Domain Graph ModelsCode0
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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