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    • Scalable Intelligence under Limited Supervision: Principles, Structures, and Adaptive Agents
    • PointNSP: Autoregressive 3D Point Cloud Generation with Next-Scale Level-of-Detail Prediction
    • Semi-supervised Instruction Tuning for Large Language Models on Text-Attributed Graphs
    • M2PG: MoE-based Adaptive Multi-Perspective Graph Fusion for Protein Representation Learning
    • Track and Tweak: Monitoring and Improving Group Fairness for Temporal Graph Neural Networks in Real Time
    • Domain-Adapted Diffusion Model for PROTAC Linker Design Through the Lens of Density Ratio in Chemical Space
    • Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification
    • FedEDM: Federated Equivariant Diffusion Model for 3D Molecule Generation with Enhanced Communication Efficiency
    • Context-aware Inductive Knowledge Graph Completion with Latent Type and Subgraph Reasoning
    • Geometric View of Soft Decorrelation in Self-Supervised Learning
    • A Systematic Survey on Federated Semi-supervised Learning
    • Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations
    • A Diffusion-based Pre-training Framework for Crystal Property Prediction
    • Tackling Long-tailed Distribution Issue in Graph Neural Networks via Normalization
    • Mitigating the Popularity Bias in Graph-based Collaborative Filtering
    • No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning
    • Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning
    • Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily
    • Towards Fair Financial Services for All: A Temporal GNN Approach for Individual Fairness on Transaction Networks
    • Contrastive Cross-scale Graph Knowledge Synergy
    • WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering
    • Graph Component Contrastive Learning for Concept Relatedness Estimation
    • SFA: Spectral Feature Augmentation for Graph Contrastive Learning
    • A Survey on Deep Semi-supervised Learning
    • Graph-based Semi-supervised Learning: A Comprehensive Review
    • COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
    • Towards an Optimal Asymmetric Graph Structure for Robust Semi-supervised Node Classification
    • Hierarchical Heterogeneous Graph Attention Network for Syntax-Aware Summarization
    • Semi-supervised Multi-label Learning for Graph-structured Data
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🎉 New homepage is live

July 2026
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Last updated on July 2026
← 🚀 IEEE CIS Task Force on Data-efficient Agentic Learning is established and is actively recruiting members July 2026