3 papers
cs.LG2025
Integrating Temporal and Structural Context in Graph Transformers for Relational Deep Learning
Divyansha Lachi, Mahmoud Mohammadi, Joe Meyer +3
In domains such as healthcare, finance, and e-commerce, the temporal dynamics of relational data emerge from complex interactions-such as those between patients and providers, or u…
cs.AI2025
RELATE: A Schema-Agnostic Perceiver Encoder for Multimodal Relational Graphs
Joe Meyer, Divyansha Lachi, Mahmoud Mohammadi +4
Relational multi-table data is common in domains such as e-commerce, healthcare, and scientific research, and can be naturally represented as heterogeneous temporal graphs with mul…
cs.LG2025
Relational Transformer: Toward Zero-Shot Foundation Models for Relational Data
Rishabh Ranjan, Valter Hudovernik, Mark Znidar +7
Pretrained transformers readily adapt to new sequence modeling tasks via zero-shot prompting, but relational domains still lack architectures that transfer across datasets and task…