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 2301–2350 of 6661 papers

TitleStatusHype
A sound description: Exploring prompt templates and class descriptions to enhance zero-shot audio classification—0
CLAWS: Contrastive Learning with hard Attention and Weak Supervision—0
Debias-CLR: A Contrastive Learning Based Debiasing Method for Algorithmic Fairness in Healthcare Applications—0
DebCSE: Rethinking Unsupervised Contrastive Sentence Embedding Learning in the Debiasing Perspective—0
A Soft Contrastive Learning-based Prompt Model for Few-shot Sentiment Analysis—0
Liquidity takers behavior representation through a contrastive learning approach—0
Graded Relevance Scoring of Written Essays with Dense Retrieval—0
DD-rPPGNet: De-interfering and Descriptive Feature Learning for Unsupervised rPPG Estimation—0
Class Relationship Embedded Learning for Source-Free Unsupervised Domain Adaptation—0
A Contrastive Learning Based Convolutional Neural Network for ERP Brain-Computer Interfaces—0
Class Prototypes Based Contrastive Learning for Classifying Multi-Label and Fine-Grained Educational Videos—0
GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling—0
DCOR: Anomaly Detection in Attributed Networks via Dual Contrastive Learning Reconstruction—0
A Generic Self-Supervised Framework of Learning Invariant Discriminative Features—0
Learning Actionable World Models for Industrial Process Control—0
Class Instance Balanced Learning for Long-Tailed Classification—0
GrabDAE: An Innovative Framework for Unsupervised Domain Adaptation Utilizing Grab-Mask and Denoise Auto-Encoder—0
Dcl-Net: Dual Contrastive Learning Network for Semi-Supervised Multi-Organ Segmentation—0
Classification of Seeds using Domain Randomization on Self-Supervised Learning Frameworks—0
A Simplifying and Learnable Graph Convolutional Attention Network for Unsupervised Knowledge Graphs Alignment—0
DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks—0
Classification of Mild Cognitive Impairment Based on Dynamic Functional Connectivity Using Spatio-Temporal Transformer—0
GNUMAP: A Parameter-Free Approach to Unsupervised Dimensionality Reduction via Graph Neural Networks—0
DAug: Diffusion-based Channel Augmentation for Radiology Image Retrieval and Classification—0
A Simplified Framework for Contrastive Learning for Node Representations—0
Classification and Clustering of Sentence-Level Embeddings of Scientific Articles Generated by Contrastive Learning—0
A Generic Method for Fine-grained Category Discovery in Natural Language Texts—0
Goal-conditioned reinforcement learning for ultrasound navigation guidance—0
DATA: Multi-Disentanglement based Contrastive Learning for Open-World Semi-Supervised Deepfake Attribution—0
CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Tasks—0
A General-Purpose Transferable Predictor for Neural Architecture Search—0
Classes Are Not Equal: An Empirical Study on Image Recognition Fairness—0
Supervised Graph Contrastive Learning for Few-shot Node Classification—0
Data-Efficient Contrastive Learning by Differentiable Hard Sample and Hard Positive Pair Generation—0
Data curation via joint example selection further accelerates multimodal learning—0
Class-aware and Augmentation-free Contrastive Learning from Label Proportion—0
3D Scene Graph Guided Vision-Language Pre-training—0
GMM-Based Comprehensive Feature Extraction and Relative Distance Preservation For Few-Shot Cross-Modal Retrieval—0
Bi-level Contrastive Learning for Knowledge-Enhanced Molecule Representations—0
Gradient-guided Unsupervised Text Style Transfer via Contrastive Learning—0
Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels—0
CLaSP: Learning Concepts for Time-Series Signals from Natural Language Supervision—0
Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noise—0
Multi-Variant Consistency based Self-supervised Learning for Robust Automatic Speech Recognition—0
ClarityEthic: Explainable Moral Judgment Utilizing Contrastive Ethical Insights from Large Language Models—0
Data Adaptive Traceback for Vision-Language Foundation Models in Image Classification—0
DashCLIP: Leveraging multimodal models for generating semantic embeddings for DoorDash—0
A General Purpose Supervisory Signal for Embodied Agents—0
DARTS: A Dual-View Attack Framework for Targeted Manipulation in Federated Sequential Recommendation—0
DART: Disease-aware Image-Text Alignment and Self-correcting Re-alignment for Trustworthy Radiology Report Generation—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