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

Showing 20012050 of 6661 papers

TitleStatusHype
Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term RetentionCode0
On the Surprising Efficacy of Distillation as an Alternative to Pre-Training Small ModelsCode0
Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive LearningCode1
Large Language Models for Expansion of Spoken Language Understanding Systems to New LanguagesCode1
GenN2N: Generative NeRF2NeRF TranslationCode2
Generative-Contrastive Heterogeneous Graph Neural NetworkCode0
Exploring the Trade-off Between Model Performance and Explanation Plausibility of Text Classifiers Using Human RationalesCode0
A Unified Membership Inference Method for Visual Self-supervised Encoder via Part-aware CapabilityCode0
CHOSEN: Contrastive Hypothesis Selection for Multi-View Depth Refinement0
ContrastCAD: Contrastive Learning-based Representation Learning for Computer-Aided Design ModelsCode1
A Universal Knowledge Embedded Contrastive Learning Framework for Hyperspectral Image ClassificationCode0
DELAN: Dual-Level Alignment for Vision-and-Language Navigation by Cross-Modal Contrastive LearningCode0
Iterated Learning Improves Compositionality in Large Vision-Language Models0
MESEN: Exploit Multimodal Data to Design Unimodal Human Activity Recognition with Few Labels0
Language Guided Domain Generalized Medical Image SegmentationCode1
SyncMask: Synchronized Attentional Masking for Fashion-centric Vision-Language Pretraining0
S2RC-GCN: A Spatial-Spectral Reliable Contrastive Graph Convolutional Network for Complex Land Cover Classification Using Hyperspectral Images0
Disentangling Hippocampal Shape Variations: A Study of Neurological Disorders Using Mesh Variational Autoencoder with Contrastive LearningCode0
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable DiffusionCode1
Heterogeneous Contrastive Learning for Foundation Models and BeyondCode1
Design as Desired: Utilizing Visual Question Answering for Multimodal Pre-trainingCode0
Classification and Clustering of Sentence-Level Embeddings of Scientific Articles Generated by Contrastive Learning0
Robust Federated Contrastive Recommender System against Model Poisoning Attack0
Heterogeneous Network Based Contrastive Learning Method for PolSAR Land Cover ClassificationCode0
Emotion-Anchored Contrastive Learning Framework for Emotion Recognition in ConversationCode1
Automatic Alignment of Discourse Relations of Different Discourse Annotation Frameworks0
FewUser: Few-Shot Social User Geolocation via Contrastive Learning0
Developing Healthcare Language Model Embedding Spaces0
PoCo: A Self-Supervised Approach via Polar Transformation Based Progressive Contrastive Learning for Ophthalmic Disease DiagnosisCode0
Siamese Vision Transformers are Scalable Audio-visual LearnersCode1
The Bad Batches: Enhancing Self-Supervised Learning in Image Classification Through Representative Batch Curation0
Mixed Preference Optimization: Reinforcement Learning with Data Selection and Better Reference Model0
PointCloud-Text Matching: Benchmark Datasets and a Baseline0
Stock Recommendations for Individual Investors: A Temporal Graph Network Approach with Mean-Variance Efficient Sampling0
Improving Content Recommendation: Knowledge Graph-Based Semantic Contrastive Learning for Diversity and Cold-Start Users0
Deep Fusion: Capturing Dependencies in Contrastive Learning via Transformer Projection Heads0
Towards Non-Exemplar Semi-Supervised Class-Incremental Learning0
Preventing Collapse in Contrastive Learning with Orthonormal Prototypes (CLOP)0
Multi-Modal Contrastive Learning for Online Clinical Time-Series Applications0
OrCo: Towards Better Generalization via Orthogonality and Contrast for Few-Shot Class-Incremental LearningCode1
NJUST-KMG at TRAC-2024 Tasks 1 and 2: Offline Harm Potential Identification0
HILL: Hierarchy-aware Information Lossless Contrastive Learning for Hierarchical Text ClassificationCode1
KDMCSE: Knowledge Distillation Multimodal Sentence Embeddings with Adaptive Angular margin Contrastive LearningCode1
EulerFormer: Sequential User Behavior Modeling with Complex Vector AttentionCode1
To Supervise or Not to Supervise: Understanding and Addressing the Key Challenges of Point Cloud Transfer Learning0
Joint enhancement of automatic chest X-ray diagnosis and radiological gaze prediction with multi-stage cooperative learning0
DreamLIP: Language-Image Pre-training with Long CaptionsCode2
Cross-lingual Contextualized Phrase RetrievalCode0
CMViM: Contrastive Masked Vim Autoencoder for 3D Multi-modal Representation Learning for AD classification0
Transfer Learning of Real Image Features with Soft Contrastive Loss for Fake Image Detection0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ResNet50ImageNet Top-1 Accuracy73.6Unverified
2ResNet50ImageNet Top-1 Accuracy73Unverified
3ResNet50ImageNet Top-1 Accuracy71.1Unverified
4ResNet50ImageNet Top-1 Accuracy69.3Unverified
5ResNet50 (v2)ImageNet Top-1 Accuracy67.6Unverified
6ResNet50 (v2)ImageNet Top-1 Accuracy63.8Unverified
7ResNet50ImageNet Top-1 Accuracy63.6Unverified
8ResNet50ImageNet Top-1 Accuracy61.5Unverified
9ResNet50ImageNet Top-1 Accuracy61.5Unverified
10ResNet50 (4×)ImageNet Top-1 Accuracy61.3Unverified
#ModelMetricClaimedVerifiedStatus
110..5sec1Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)84.77Unverified
#ModelMetricClaimedVerifiedStatus
1IPCL (ResNet18)Accuracy (Top-1)85.55Unverified