ReSS Framework Combines Symbolic and Neural Models for Tabular Data Prediction
Researchers introduce ReSS, a hybrid framework that merges symbolic and neural models to improve tabular data prediction. The approach aims to enhance both accuracy and human-understandable reasoning in high-stakes domains like healthcare and finance.