All Stories

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