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 2201–2250 of 6661 papers

TitleStatusHype
A-MESS: Anchor based Multimodal Embedding with Semantic Synchronization for Multimodal Intent Recognition—0
On the Perception Bottleneck of VLMs for Chart UnderstandingCode0
OCCO: LVM-guided Infrared and Visible Image Fusion Framework based on Object-aware and Contextual COntrastive Learning—0
Structuring Scientific Innovation: A Framework for Modeling and Discovering Impactful Knowledge Combinations—0
RoCA: Robust Contrastive One-class Time Series Anomaly Detection with Contaminated DataCode0
Anchor-based oversampling for imbalanced tabular data via contrastive and adversarial learning—0
Unsupervised Detection of Fraudulent Transactions in E-commerce Using Contrastive Learning—0
Recommendation System in Advertising and Streaming Media: Unsupervised Data Enhancement Sequence Suggestions—0
Does GCL Need a Large Number of Negative Samples? Enhancing Graph Contrastive Learning with Effective and Efficient Negative SamplingCode0
What Time Tells Us? An Explorative Study of Time Awareness Learned from Static Images—0
Enhancing Persona Consistency for LLMs' Role-Playing using Persona-Aware Contrastive Learning—0
NaFM: Pre-training a Foundation Model for Small-Molecule Natural ProductsCode0
Generative Modeling of Class Probability for Multi-Modal Representation Learning—0
Should we pre-train a decoder in contrastive learning for dense prediction tasks?—0
A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics—0
Neural-Guided Equation DiscoveryCode0
Federated Cross-Domain Click-Through Rate Prediction With Large Language Model Augmentation—0
Semi-supervised Cervical Segmentation on Ultrasound by A Dual Framework for Neural NetworksCode0
DocVideoQA: Towards Comprehensive Understanding of Document-Centric Videos through Question Answering—0
Diffusion-augmented Graph Contrastive Learning for Collaborative Filter—0
UniSync: A Unified Framework for Audio-Visual Synchronization—0
GAIR: Improving Multimodal Geo-Foundation Model with Geo-Aligned Implicit Representations—0
Beyond the Visible: Multispectral Vision-Language Learning for Earth Observation—0
PromptHash: Affinity-Prompted Collaborative Cross-Modal Learning for Adaptive Hashing RetrievalCode0
Unlocking the Capabilities of Vision-Language Models for Generalizable and Explainable Deepfake Detection—0
TULIP: Towards Unified Language-Image Pretraining—0
Machine Unlearning in Hyperbolic vs. Euclidean Multimodal Contrastive Learning: Adapting Alignment Calibration to MERUCode0
Graph-Weighted Contrastive Learning for Semi-Supervised Hyperspectral Image ClassificationCode0
Continual Multimodal Contrastive Learning—0
Text-Derived Relational Graph-Enhanced Network for Skeleton-Based Action SegmentationCode0
EgoDTM: Towards 3D-Aware Egocentric Video-Language PretrainingCode0
DashCLIP: Leveraging multimodal models for generating semantic embeddings for DoorDash—0
HySurvPred: Multimodal Hyperbolic Embedding with Angle-Aware Hierarchical Contrastive Learning and Uncertainty Constraints for Survival Prediction—0
Incorporating Attributes and Multi-Scale Structures for Heterogeneous Graph Contrastive Learning—0
DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabularies—0
Robust Audio-Visual Segmentation via Audio-Guided Visual Convergent Alignment—0
A Survey on Self-supervised Contrastive Learning for Multimodal Text-Image Analysis—0
Unicorn: A Universal and Collaborative Reinforcement Learning Approach Towards Generalizable Network-Wide Traffic Signal Control—0
Technical Approach for the EMI Challenge in the 8th Affective Behavior Analysis in-the-Wild Competition—0
TacticExpert: Spatial-Temporal Graph Language Model for Basketball Tactics—0
RankPO: Preference Optimization for Job-Talent MatchingCode0
OuroMamba: A Data-Free Quantization Framework for Vision Mamba Models—0
SOLA-GCL: Subgraph-Oriented Learnable Augmentation Method for Graph Contrastive Learning—0
Bilingual Dual-Head Deep Model for Parkinson's Disease Detection from SpeechCode0
Enhance Exploration in Safe Reinforcement Learning with Contrastive Representation Learning—0
Robust Asymmetric Heterogeneous Federated Learning with Corrupted ClientsCode0
Domain Adaptation for Japanese Sentence Embeddings with Contrastive Learning based on Synthetic Sentence GenerationCode0
Towards Robust Multimodal Representation: A Unified Approach with Adaptive Experts and AlignmentCode0
Diff-CL: A Novel Cross Pseudo-Supervision Method for Semi-supervised Medical Image Segmentation—0
Decoupled Doubly Contrastive Learning for Cross Domain Facial Action Unit Detection—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