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 1201–1250 of 6661 papers

TitleStatusHype
Exploring Multimodal Approaches for Alzheimer's Disease Detection Using Patient Speech Transcript and Audio DataCode1
Learning Representation for Clustering via Prototype Scattering and Positive SamplingCode1
Automatically Generating Numerous Context-Driven SFT Data for LLMs across Diverse GranularityCode1
Beyond Co-occurrence: Multi-modal Session-based RecommendationCode1
Contrastive Learning for Knowledge TracingCode1
Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence EmbeddingCode1
Beyond Known Clusters: Probe New Prototypes for Efficient Generalized Class DiscoveryCode1
Contrastive Learning of Musical RepresentationsCode1
Adaptive Supervised PatchNCE Loss for Learning H&E-to-IHC Stain Translation with Inconsistent Groundtruth Image PairsCode1
Contrastive Fine-grained Class Clustering via Generative Adversarial NetworksCode1
Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure LearningCode1
FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive LearningCode1
Alleviating Over-smoothing for Unsupervised Sentence RepresentationCode1
FaMeSumm: Investigating and Improving Faithfulness of Medical SummarizationCode1
Contrastive Learning of Sentence Embeddings from ScratchCode1
FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot DetectionCode1
FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image ClassificationCode1
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial RobustnessCode1
Conditional Contrastive Learning with KernelCode1
Few-Shot Intent Detection via Contrastive Pre-Training and Fine-TuningCode1
FiGURe: Simple and Efficient Unsupervised Node Representations with Filter AugmentationsCode1
Filtering, Distillation, and Hard Negatives for Vision-Language Pre-TrainingCode1
Contrastive Grouping with Transformer for Referring Image SegmentationCode1
AD-CLIP: Adapting Domains in Prompt Space Using CLIPCode1
Contrastive Identity-Aware Learning for Multi-Agent Value DecompositionCode1
Fine-grained Temporal Contrastive Learning for Weakly-supervised Temporal Action LocalizationCode1
Automated Spatio-Temporal Graph Contrastive LearningCode1
Decoupled Contrastive LearningCode1
Contrastive Label Disambiguation for Partial Label LearningCode1
Big Self-Supervised Models Advance Medical Image ClassificationCode1
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable DiffusionCode1
Contrastive Learning Reduces Hallucination in ConversationsCode1
ConDA: Contrastive Domain Adaptation for AI-generated Text DetectionCode1
Contrastive Laplacian EigenmapsCode1
Frame-wise Action Representations for Long Videos via Sequence Contrastive LearningCode1
Contrastive Learning of User Behavior Sequence for Context-Aware Document RankingCode1
Frequency-Based Alignment of EEG and Audio Signals Using Contrastive Learning and SincNet for Auditory Attention DetectionCode1
Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input RepresentationCode1
Contrastive Learning for Improving ASR Robustness in Spoken Language UnderstandingCode1
Alleviating Exposure Bias via Contrastive Learning for Abstractive Text SummarizationCode1
From Real to Cloned Singer IdentificationCode1
ProGCL: Rethinking Hard Negative Mining in Graph Contrastive LearningCode1
g3D-LF: Generalizable 3D-Language Feature Fields for Embodied TasksCode1
GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait RecognitionCode1
DeCLUTR: Deep Contrastive Learning for Unsupervised Textual RepresentationsCode1
Contrastive Learning-Based Audio to Lyrics Alignment for Multiple LanguagesCode1
Debiased Contrastive LearningCode1
Automated Essay Scoring via Pairwise Contrastive RegressionCode1
A Unified Generative Framework for Realistic Lidar Simulation in Autonomous Driving SystemsCode1
Debiased Contrastive Learning for Sequential RecommendationCode1
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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