RGRS is proposed, a unified neuro-symbolic framework that integrates rule-level reasoning with graph representation learning for scalable Horn rule instantiation and achieves consistently high accuracy with significant efficiency gains over symbolic and neuro-symbolic baselines.
Tian Li, Xueli Liu, Bo-Wen Dong et al.· Proceedings of the 32nd ACM...· 0 citations
This study develops an explainable machine learning framework for modeling loan approval decisions on heterogeneous tabular data, centered on a Cross-Attentional Tabular Transformer that applies bidirectional cross-attention between numerical and categorical feature groups.
Bowen Dong, Xinyu Zhang, Ziwei Hong et al.· Entropy· 0 citations
RGRS is proposed, a unified neuro-symbolic framework that integrates rule-level reasoning with graph representation learning for scalable Horn rule instantiation and achieves consistently high accuracy with significant efficiency gains over symbolic and neuro-symbolic baselines.
Tian Li, Xueli Liu, Bowen Dong et al.· Proceedings of the 32nd ACM...· 0 citations
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