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 6051–6100 of 6661 papers

TitleStatusHype
Idempotent Unsupervised Representation Learning for Skeleton-Based Action RecognitionCode0
Spectrum Translation for Refinement of Image Generation (STIG) Based on Contrastive Learning and Spectral Filter ProfileCode0
Acoustic word embeddings for zero-resource languages using self-supervised contrastive learning and multilingual adaptationCode0
IDEAL: Improved DEnse locAL Contrastive Learning for Semi-Supervised Medical Image SegmentationCode0
Speech Analysis of Language Varieties in ItalyCode0
Projection Head is Secretly an Information BottleneckCode0
Adversarial Learning Data Augmentation for Graph Contrastive Learning in RecommendationCode0
Unsupervised Natural Language Inference via Decoupled Multimodal Contrastive LearningCode0
CLAP. I. Resolving miscalibration for deep learning-based galaxy photometric redshift estimationCode0
Adversarial Graph Contrastive Learning with Information RegularizationCode0
Unsupervised Person Re-identification with Stochastic Training StrategyCode0
HyperTrack: Neural Combinatorics for High Energy PhysicsCode0
PromptCL: Improving Event Representation via Prompt Template and Contrastive LearningCode0
Traffic Forecasting on New Roads Using Spatial Contrastive Pre-Training (SCPT)Code0
Spherical Space Feature Decomposition for Guided Depth Map Super-ResolutionCode0
Contrastive Learning in Distilled ModelsCode0
Hyperspectral Image Classification With Contrastive Graph Convolutional NetworkCode0
Prompt-enhanced Network for Hateful Meme ClassificationCode0
A Self-explaining Neural Architecture for Generalizable Concept LearningCode0
Artifact-Tolerant Clustering-Guided Contrastive Embedding Learning for Ophthalmic ImagesCode0
PromptHash: Affinity-Prompted Collaborative Cross-Modal Learning for Adaptive Hashing RetrievalCode0
PromptHash:Affinity-Prompted Collaborative Cross-Modal Learning for Adaptive Hashing RetrievalCode0
Training Class-Imbalanced Diffusion Model Via Overlap OptimizationCode0
Prompting Vision-Language Model for Nuclei Instance Segmentation and ClassificationCode0
HU at SemEval-2024 Task 8A: Can Contrastive Learning Learn Embeddings to Detect Machine-Generated Text?Code0
Splicing Up Your Predictions with RNA Contrastive LearningCode0
Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural NetworksCode0
ARIEL: Adversarial Graph Contrastive LearningCode0
Inter-intra Variant Dual Representations forSelf-supervised Video RecognitionCode0
Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive LearningCode0
CLAD: A Contrastive Learning based Approach for Background DebiasingCode0
Hierarchical Semi-Supervised Contrastive Learning for Contamination-Resistant Anomaly DetectionCode0
Hierarchical Intent-guided Optimization with Pluggable LLM-Driven Semantics for Session-based RecommendationCode0
HierarchicalContrast: A Coarse-to-Fine Contrastive Learning Framework for Cross-Domain Zero-Shot Slot FillingCode0
ProtFAD: Introducing function-aware domains as implicit modality towards protein function predictionCode0
Squeeze and Excitation: A Weighted Graph Contrastive Learning for Collaborative FilteringCode0
Hierarchical Context Transformer for Multi-level Semantic Scene UnderstandingCode0
HICL: Hashtag-Driven In-Context Learning for Social Media Natural Language UnderstandingCode0
Contrastive Learning for Task-Independent SpeechLLM-PretrainingCode0
CKD: Contrastive Knowledge Distillation from A Sample-wise PerspectiveCode0
CiPR: An Efficient Framework with Cross-instance Positive Relations for Generalized Category DiscoveryCode0
SSCL-IDS: Enhancing Generalization of Intrusion Detection with Self-Supervised Contrastive LearningCode0
Prototypical Contrast Adaptation for Domain Adaptive Semantic SegmentationCode0
Train Once for All: A Transitional Approach for Efficient Aspect Sentiment Triplet ExtractionCode0
Heterogeneous Tri-stream Clustering NetworkCode0
Heterogeneous Social Event Detection via Hyperbolic Graph RepresentationsCode0
Heterogeneous network drug-target interaction prediction model based on graph wavelet transform and multi-level contrastive learningCode0
Contrastive Learning for Sleep Staging based on Inter Subject CorrelationCode0
Contrastive Learning for Predicting Cancer Prognosis Using Gene Expression ValuesCode0
Heterogeneous Network Based Contrastive Learning Method for PolSAR Land Cover ClassificationCode0
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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