All Stories

  1. AgentDR: Dynamic Recommendation with Implicit Item-Item Relations via LLM-based Agents
  2. GraFS: An Integrated GNN-LLM Approach for Inferring Best Functional Substitute Products
  3. Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation
  4. Covering a Graph with Dense Subgraph Families, via Triangle-Rich Sets
  5. Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training
  6. An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-Commerce
  7. ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding
  8. Search Behavior Prediction: A Hypergraph Perspective
  9. Hyperbolic Neural Networks: Theory, Architectures and Applications
  10. Graph-based Multilingual Language Model
  11. Learning Backward Compatible Embeddings
  12. ALLIE: Active Learning on Large-scale Imbalanced Graphs
  13. Accepted Tutorials at The Web Conference 2022
  14. ANTHEM
  15. Bipartite Dynamic Representations for Abuse Detection
  16. Using hyperboloids to embed and query knowledge graphs
  17. Identifying Facet Mismatches In Search Via Micrographs