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 2101–2150 of 6661 papers

TitleStatusHype
OmicsCL: Unsupervised Contrastive Learning for Cancer Subtype Discovery and Survival StratificationCode0
SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End DevicesCode0
Exploring internal representation of self-supervised networks: few-shot learning abilities and comparison with human semantics and recognition of objects—0
DB-GNN: Dual-Branch Graph Neural Network with Multi-Level Contrastive Learning for Jointly Identifying Within- and Cross-Frequency Coupled Brain Networks—0
ISDrama: Immersive Spatial Drama Generation through Multimodal Prompting—0
ClearVision: Leveraging CycleGAN and SigLIP-2 for Robust All-Weather Classification in Traffic Camera Imagery—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
Heterogeneous network drug-target interaction prediction model based on graph wavelet transform and multi-level contrastive learningCode0
Combating the Bucket Effect:Multi-Knowledge Alignment for Medication Recommendation—0
I-Con: A Unifying Framework for Representation Learning—0
OmniSage: Large Scale, Multi-Entity Heterogeneous Graph Representation Learning—0
Improving Sound Source Localization with Joint Slot Attention on Image and Audio—0
Survey of Loss Augmented Knowledge Tracing—0
Dynamic Contrastive Skill Learning with State-Transition Based Skill Clustering and Dynamic Length Adjustment—0
sEEG-based Encoding for Sentence Retrieval: A Contrastive Learning Approach to Brain-Language Alignment—0
SuperCL: Superpixel Guided Contrastive Learning for Medical Image Segmentation Pre-training—0
DConAD: A Differencing-based Contrastive Representation Learning Framework for Time Series Anomaly DetectionCode0
Towards NSFW-Free Text-to-Image Generation via Safety-Constraint Direct Preference Optimization—0
Human-aligned Deep Learning: Explainability, Causality, and Biological Inspiration—0
Transformation of audio embeddings into interpretable, concept-based representations—0
Consensus-aware Contrastive Learning for Group Recommendation—0
CM3AE: A Unified RGB Frame and Event-Voxel/-Frame Pre-training FrameworkCode0
Machine Learning Methods for Gene Regulatory Network Inference—0
PSG-MAE: Robust Multitask Sleep Event Monitoring using Multichannel PSG Reconstruction and Inter-channel Contrastive Learning—0
The Others: Naturally Isolating Out-of-Distribution Samples for Robust Open-Set Semi-Supervised Learning—0
FedEPA: Enhancing Personalization and Modality Alignment in Multimodal Federated Learning—0
DART: Disease-aware Image-Text Alignment and Self-correcting Re-alignment for Trustworthy Radiology Report Generation—0
CAGS: Open-Vocabulary 3D Scene Understanding with Context-Aware Gaussian Splatting—0
SALAD: Improving Robustness and Generalization through Contrastive Learning with Structure-Aware and LLM-Driven Augmented Data—0
Balancing Graph Embedding Smoothness in Self-Supervised Learning via Information-Theoretic DecompositionCode0
TMCIR: Token Merge Benefits Composed Image Retrieval—0
How to Enhance Downstream Adversarial Robustness (almost) without Touching the Pre-Trained Foundation Model?—0
AFiRe: Anatomy-Driven Self-Supervised Learning for Fine-Grained Representation in Radiographic ImagesCode0
Subset-Contrastive Multi-Omics Network Embedding—0
OpenTuringBench: An Open-Model-based Benchmark and Framework for Machine-Generated Text Detection and Attribution—0
PARTFIELD: Learning 3D Feature Fields for Part Segmentation and Beyond—0
AimTS: Augmented Series and Image Contrastive Learning for Time Series Classification—0
Controllable Expressive 3D Facial Animation via Diffusion in a Unified Multimodal Space—0
On the Value of Cross-Modal Misalignment in Multimodal Representation LearningCode0
STaRFormer: Semi-Supervised Task-Informed Representation Learning via Dynamic Attention-Based Regional Masking for Sequential Data—0
Causal integration of chemical structures improves representations of microscopy images for morphological profilingCode0
Multi-Modal Hypergraph Enhanced LLM Learning for Recommendation—0
FSSUAVL: A Discriminative Framework using Vision Models for Federated Self-Supervised Audio and Image Understanding—0
Federated Prototype Graph Learning—0
FairACE: Achieving Degree Fairness in Graph Neural Networks via Contrastive and Adversarial Group-Balanced Training—0
CMIP-CIL: A Cross-Modal Benchmark for Image-Point Class Incremental LearningCode0
Embodied Image Captioning: Self-supervised Learning Agents for Spatially Coherent Image Descriptions—0
Impact of Language Guidance: A Reproducibility Study—0
RadZero: Similarity-Based Cross-Attention for Explainable Vision-Language Alignment in Radiology with Zero-Shot Multi-Task Capability—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