AI RESEARCH
TN-SHAP-G: Graph-Structured Tensor Network Surrogates for Shapley Values and Interactions
arXiv CS.AI
•
ArXi:2606.01540v1 Announce Type: cross Shapley values are a widely used tool for attributing importance and interactions among input variables in black-box models, but their computation involves a function defined over an exponentially large space of subsets. We propose TN-SHAP-G, a framework that exploits structure in graph-structured inputs to compute Shapley values and higher-order interaction indices efficiently.