Grables: When Graph Structure Helps Tabular Prediction
Row-wise predictors are limited because they cannot capture targets dependent on other rows, like relational patterns or global counts. The paper introduces 'grables,' a modular interface separating how data is turned into a graph (constructor) from how predictions are made on that graph (node predictor). This framework reveals when using explicit inter-row structure is necessary for complex tabular tasks.