🔗 Talk Details & Schedule

Detailed Program

Current schedule. The program may be updated before the workshop.

  • 08:00 am - 08:10 am
    Opening & Introduction
  • 08:10 am - 08:50 am
    Keynote Talk 1
    Irwin King, "Hyperbolic Learning in the Large Model Era"
  • 08:50 am - 09:30 am
    Keynote Talk 2
    Nitesh Chawla
  • 09:30 am - 10:00 am
    Coffee Break & Poster Presentation
  • 10:00 am - 10:40 am
    Keynote Talk 3
    Hanghang Tong
  • 10:40 am - 11:20 am
    Keynote Talk 4
    Yizhou Sun, "Deep Graph Learning for Dynamical Systems"
  • 11:20 am - 12:00 am
    Award & Oral Presentation
    • AdaTKG: Adaptive Memory for Temporal Knowledge Graph Reasoning
    • GraphMind: Empowering LLMs for Interactive Graph Structure Reasoning with Semi-Formal Language
    • SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory
    • GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning
    • Learning Faithful Mechanism Subgraphs from Partially Trusted Biological Priors for Genetic Perturbation Prediction
  • 12:00 am - 12:10 pm
    Closing & Acknowledgment

Speakers

Irwin King

Irwin King

Professor at The Chinese University of Hong Kong. He is a fellow of ACM, IEEE, AAAI and INNS.

Nitesh Chawla

Nitesh Chawla

Professor at University of Notre Dame. He is a Fellow of AAAI, AAAS, ACM, and IEEE.

Hanghang Tong

Hanghang Tong

Professor at UIUC. He is a fellow of ACM and IEEE, a senior member of AAAI, and a university scholar of UIUC.

Yizhou Sun

Yizhou Sun

Professor at UCLA. Her Google citation count is over 30k. KDD PC Co-Chair, 2025; ICLR PC Co-Chair, 2024; KDD General Co-Chair, 2023, etc.

Accepted Papers

🎤 Oral

  • AdaTKG: Adaptive Memory for Temporal Knowledge Graph Reasoning
  • GraphMind: Empowering LLMs for Interactive Graph Structure Reasoning with Semi-Formal Language
  • SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory
  • GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning
  • Learning Faithful Mechanism Subgraphs from Partially Trusted Biological Priors for Genetic Perturbation Prediction

📌 Poster

  • Adaptive Self-Interference Control for Large Heterophilic Graphs
  • CMERGE: Clinical Multimodal Evidence Reasoning Graph Engine
  • CondPSE: A Polynomial-Filtered Structural Encoder with Conditional Modulation for Graphs
  • WarehouseAI: Knowledge Graph-Grounded Multi-Agent Reasoning Framework for Simulation-Driven Warehouse Planning
  • When Drug Names Mislead: Auditing Name-Prior Reliance in LLM-Augmented Biomedical Graph Completion
  • Bridging Circuit Graphs and Language: A Cross-Modal Transformer for Netlist-to-Text Alignment and Generation
  • Measuring Graph-to-Graph Semantic Similarity in Knowledge Graphs: An Empirical Evaluation of Knowledge Graph Embeddings