Awesome Self-Supervised & Contrastive

Key papers

• Graph Neural Networks in Modern AI-aided Drug Discovery (2025)
  Odin Zhang et al.
  8.75
• Social Network User Profiling for Anomaly Detection Based on Graph Neural Networks (2025)
  Yiwei Zhang
  6.69
• Incorporating Attributes and Multi-Scale Structures for Heterogeneous Graph Contrastive Learning (2025)
  Ruobing Jiang et al.
  6.23
• CureGraph: Contrastive Multi-Modal Graph Representation Learning for Urban Living Circle Health Profiling and Prediction (2025)
  Jinlin Li et al.
  6.12
• Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention (2025)
  Van Thuy Hoang et al.
  5.35
• Molecular Graph Contrastive Learning with Line Graph (2025)
  Xueyuan Chen et al.
  5.18
• Balancing Graph Embedding Smoothness in Self-Supervised Learning via Information-Theoretic Decomposition (2025)
  Heesoo Jung et al.
  4.93
• SpliceBind: Isoform-Aware Prediction of Binding Pocket Druggability (2026)
  Bryan Cheng et al.
  4.39
• Structure-Aware Prediction of PROTAC-Mediated Protein Degradability via Graph Neural Networks (2026)
  Bryan Cheng et al.
  4.39
• Revisiting Positive Samples in Graph Contrastive Learning: From the Perspective of Message Passing (2026)
  Lianze Shan et al.
  4.39
• ERAlign: Energy-based Representation Alignment of GNNs and LLMs on Text-attributed Graphs (2026)
  Xianlin Zeng et al.
  4.39
• GLACIER: A Multimodal Student-Teacher Foundation Model for Molecular Property Prediction (2026)
  Emily Nguyen et al.
  4.39
• LLMs+Graphs: Toward Graph-Native, Synergistic AI Systems (2026)
  Arijit Khan et al.
  4.39
• TMR-GGNN: Credit Card Fraud Detection based on Time-Aware Multi-Relational Guided Graph Neural Network (2026)
  Rohit Tewari et al.
  4.39
• GOProteinGNN: Leveraging Protein Knowledge Graphs for Protein Representation Learning (2024)
  Dan Kalifa et al.
  4.36
• CIMAGE: Exploiting the Conditional Independence in Masked Graph Auto-encoders (2025)
  Jongwon Park et al.
  4.36
• Fast and Featureless Node Representation Learning with Partial Pairwise Supervision (2026)
  Sujan Chakraborty et al.
  4.33
• Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification (2026)
  Brown Zaz et al.
  4.33
• Instance Discrimination for Link Prediction (2026)
  Valentin Cuzin-Rambaud (SyCoSMA et al.
  4.33
• EvoStruct: Bridging Evolutionary and Structural Priors for Antibody CDR Design via Protein Language Model Adaptation (2026)
  Mansoor Ahmed et al.
  4.33
• Self-supervised Adversarial Purification for Graph Neural Networks (2026)
  Woohyun Lee et al.
  4.33
• Advancing Graph Few-Shot Learning via In-Context Learning (2026)
  Renchu Guan et al.
  4.33
• Beyond the Aggregation Dilemma: Prior-Retaining Decoupled Learning for Multimodal Graphs (2026)
  Hao Yan et al.
  4.33
• Capture-Calibrate-Coach: A Graph-Based Framework for Knowledge Monitoring Estimation and Adaptive Feedback (2026)
  Gen Li et al.
  4.33
• L2IR: Revealing Latent Intent in Graph Fraud Detection (2026)
  Jinsheng Guo et al.
  4.33
• Generalist Graph Anomaly Detection via Prototype-Based Distillation (2026)
  Yiming Xu et al.
  4.33
• Learning Dynamic Graph Representations through Timespan View Contrasts (2026)
  Yiming Xu et al.
  4.33
• Where LLM Annotators Fail: Label-Free Learning on Graphs with LLMs (2026)
  Safal Thapaliya et al.
  4.33
• Robust Contrastive Graph Clustering with Adaptive Local-Global Integration (2026)
  Lei Zhang et al.
  4.33
• UniGraph2: Learning a Unified Embedding Space to Bind Multimodal Graphs (2025)
  Yufei He et al.
  4.30
• RankGraph: Unified Heterogeneous Graph Learning for Cross-Domain Recommendation (2025)
  Renzhi Wu and Junjie Yang and Li Chen and Hong Li and Li Yu and Hong Yan
  4.03
• Unsupervised Graph Clustering with Deep Structural Entropy (2025)
  Jingyun Zhang et al.
  3.81
• SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval (2025)
  Nikolaos Chaidos et al.
  3.81
• Graph Positional Autoencoders as Self-supervised Learners (2025)
  Yang Liu et al.
  3.81
• Hierarchical Vector Quantized Graph Autoencoder with Annealing-Based Code Selection (2025)
  Long Zeng et al.
  3.75
• SOLA-GCL: Subgraph-Oriented Learnable Augmentation Method for Graph Contrastive Learning (2025)
  Tianhao Peng et al.
  3.70
• Does GCL Need a Large Number of Negative Samples? Enhancing Graph Contrastive Learning with Effective and Efficient Negative Sampling (2025)
  Yongqi Huang et al.
  3.70
• TabGLM: Tabular Graph Language Model for Learning Transferable Representations Through Multi-Modal Consistency Minimization (2025)
  Anay Majee and Maria Xenochristou and Wei-Peng Chen
  3.64
• Graph Contrastive Learning on Multi-label Classification for Recommendations (2025)
  Jiayang Wu et al.
  3.59
• Peptide2Mol: A Diffusion Model for Generating Small Molecules as Peptide Mimics for Targeted Protein Binding (2025)
  Xinheng He et al.
  3.21
• MCFCN: Multi-View Clustering via a Fusion-Consensus Graph Convolutional Network (2025)
  Chenping Pei et al.
  3.21
• Revisiting and Benchmarking Graph Autoencoders: A Contrastive Learning Perspective (2024)
  Jintang Li et al.
  3.20
• A Re-node Self-training Approach for Deep Graph-based Semi-supervised Classification on Multi-view Image Data (2025)
  Jingjun Bi et al.
  3.15
• FireGNN: Neuro-Symbolic Graph Neural Networks with Trainable Fuzzy Rules for Interpretable Medical Image Classification (2025)
  Prajit Sengupta and Islem Rekik
  3.10
• Property-Isometric Variational Autoencoders for Sequence Modeling and Design (2025)
  Elham Sadeghi et al.
  3.10
• NTSFormer: A Self-Teaching Graph Transformer for Multimodal Isolated Cold-Start Node Classification (2025)
  Jun Hu et al.
  2.99
• Heterogeneous Graph Prompt Learning via Adaptive Weight Pruning (2025)
  Chu-Yuan Wei et al.
  2.99
• Attributed Graph Clustering with Multi-Scale Weight-Based Pairwise Coarsening and Contrastive Learning (2025)
  Binxiong Li et al.
  2.99
• CLGNN: A Contrastive Learning-based GNN Model for Betweenness Centrality Prediction on Temporal Graphs (2025)
  Tianming Zhang et al.
  2.93
• Rethinking Graph Contrastive Learning through Relative Similarity Preservation (2025)
  Zhiyuan Ning et al.
  2.87
• Next Word Suggestion using Graph Neural Network (2025)
  Abisha Thapa Magar et al.
  2.87
• Understanding the Capabilities of Molecular Graph Neural Networks in Materials Science Through Multimodal Learning and Physical Context Encoding (2025)
  Can Polat et al.
  2.87
• LL4G: Self-Supervised Dynamic Optimization for Graph-Based Personality Detection (2025)
  Lingzhi Shen et al.
  2.82
• Pre-training Graph Neural Networks with Structural Fingerprints for Materials Discovery (2025)
  Shuyi Jia et al.
  2.76
• LLM-Empowered Class Imbalanced Graph Prompt Learning for Online Drug Trafficking Detection (2025)
  Tianyi Ma et al.
  2.76
• GMLM: Bridging Graph Neural Networks and Language Models for Heterophilic Node Classification (2025)
  Aarush Sinha
  2.76
• TacticExpert: Spatial-Temporal Graph Language Model for Basketball Tactics (2025)
  Xu Lingrui et al.
  2.76
• AugWard: Augmentation-Aware Representation Learning for Accurate Graph Classification (2025)
  Minjun Kim et al.
  2.76
• Accelerating High-Efficiency Organic Photovoltaic Discovery via Pretrained Graph Neural Networks and Generative Reinforcement Learning (2025)
  Jiangjie Qiu et al.
  2.76
• Graph-based Molecular In-context Learning Grounded on Morgan Fingerprints (2025)
  Ali Al-Lawati et al.
  2.71