Chu-Lei Xiang

GLoT: global–local token alignment for interpretable zero-shot graph reasoning with LLMs for e-commerce applications

A two-stage framework that tightly couples self-supervised graph learning with dual-projection prompting that guarantees that local context is derived from the same clustering signal used during pretraining, and global and local semantics are aligned through purpose-built pathways is proposed.