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 201–250 of 6661 papers

TitleStatusHype
Robust Federated Learning on Edge Devices with Domain Heterogeneity—0
Reinforced Interactive Continual Learning via Real-time Noisy Human Feedback—0
Instance-Prototype Affinity Learning for Non-Exemplar Continual Graph Learning—0
Negative Metric Learning for Graphs—0
Large Wireless Localization Model (LWLM): A Foundation Model for Positioning in 6G NetworksCode1
A Unified and Scalable Membership Inference Method for Visual Self-supervised Encoder via Part-aware CapabilityCode0
MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological AssessmentCode1
Unsupervised Multiview Contrastive Language-Image Joint Learning with Pseudo-Labeled Prompts Via Vision-Language Model for 3D/4D Facial Expression Recognition—0
A Multi-Task Foundation Model for Wireless Channel Representation Using Contrastive and Masked Autoencoder Learning—0
Endo-CLIP: Progressive Self-Supervised Pre-training on Raw Colonoscopy Records—0
DFA-CON: A Contrastive Learning Approach for Detecting Copyright Infringement in DeepFake Art—0
Hyperbolic Contrastive Learning with Model-augmentation for Knowledge-aware RecommendationCode1
Improving Unsupervised Task-driven Models of Ventral Visual Stream via Relative Position PredictivityCode0
Self-Supervised Transformer-based Contrastive Learning for Intrusion Detection SystemsCode0
Pre-training vs. Fine-tuning: A Reproducibility Study on Dense Retrieval Knowledge AcquisitionCode0
FedIFL: A federated cross-domain diagnostic framework for motor-driven systems with inconsistent fault modes—0
EAGLE: Contrastive Learning for Efficient Graph Anomaly Detection—0
A Vision-Language Foundation Model for Leaf Disease IdentificationCode0
Image Classification Using a Diffusion Model as a Pre-Training Model—0
Multimodal Fake News Detection: MFND Dataset and Shallow-Deep Multitask LearningCode1
MarkMatch: Same-Hand Stuffing Detection—0
Joint Low-level and High-level Textual Representation Learning with Multiple Masking Strategies—0
Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling LawsCode0
Weakly Supervised Temporal Sentence Grounding via Positive Sample Mining—0
Towards Robust Few-Shot Text Classification Using Transformer Architectures and Dual Loss Strategies—0
Enhanced Urdu Intent Detection with Large Language Models and Prototype-Informed Predictive Pipelines—0
Rethinking Graph Contrastive Learning through Relative Similarity Preservation—0
VaCDA: Variational Contrastive Alignment-based Scalable Human Activity Recognition—0
Generalization Analysis for Contrastive Representation Learning under Non-IID Settings—0
HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights—0
DATA: Multi-Disentanglement based Contrastive Learning for Open-World Semi-Supervised Deepfake Attribution—0
STG: Spatiotemporal Graph Neural Network with Fusion and Spatiotemporal Decoupling Learning for Prognostic Prediction of Colorectal Cancer Liver Metastasis—0
Path and Bone-Contour Regularized Unpaired MRI-to-CT TranslationCode0
Generative Sign-description Prompts with Multi-positive Contrastive Learning for Sign Language Recognition—0
JTCSE: Joint Tensor-Modulus Constraints and Cross-Attention for Unsupervised Contrastive Learning of Sentence EmbeddingsCode0
VAEmo: Efficient Representation Learning for Visual-Audio Emotion with Knowledge InjectionCode0
ProDisc-VAD: An Efficient System for Weakly-Supervised Anomaly Detection in Video Surveillance ApplicationsCode1
Intelligently Augmented Contrastive Tensor Factorization: Empowering Multi-dimensional Time Series Classification in Low-Data Environments—0
Weakly-supervised Audio Temporal Forgery Localization via Progressive Audio-language Co-learning NetworkCode0
An LLM-Empowered Low-Resolution Vision System for On-Device Human Behavior Understanding—0
SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End DevicesCode0
OmicsCL: Unsupervised Contrastive Learning for Cancer Subtype Discovery and Survival StratificationCode0
CSE-SFP: Enabling Unsupervised Sentence Representation Learning via a Single Forward Pass—0
Recursive KL Divergence Optimization: A Dynamic Framework for Representation LearningCode1
DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks—0
Exploring internal representation of self-supervised networks: few-shot learning abilities and comparison with human semantics and recognition of objects—0
ISDrama: Immersive Spatial Drama Generation through Multimodal Prompting—0
VCM: Vision Concept Modeling Based on Implicit Contrastive Learning with Vision-Language Instruction Fine-Tuning—0
Masked Point-Entity Contrast for Open-Vocabulary 3D Scene Understanding—0
ClearVision: Leveraging CycleGAN and SigLIP-2 for Robust All-Weather Classification in Traffic Camera Imagery—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