Latent Bridges for Multi-Table Question Answering
GRAB introduces a pipeline for table question answering that converts relational data into a heterogeneous graph, encodes it using message passing, and transfers information to a frozen LLM via query-conditioned latent tokens. This method lifts structural relationships from tables, allowing the system to handle complex multi-table queries more effectively than text serialization alone.