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Yi Qiao

2 accepted papers

2026

Behavior Tokens Speak Louder: Disentangled Explainable Recommendation with Behavior Vocabulary

AAAI 2026technical

Recent advances in explainable recommendation have explored the integration of language models to analyze natural language rationales for user–item interactions. Despite their potential, existing methods often rely on ID-based representations that obscure semantic meaning and impose structural const

Cited by 0SourcePDFScholar
2025

Domain-aware Node Representation Learning for Graph Out-of-Distribution Generalization

ICASSP 2025accepted

Graph Neural Networks (GNNs) have demonstrated impressive success across diverse fields when data satisfies in-distribution (ID) assumption. Nevertheless, GNN performance significantly declines in cases of distribution shifts between training and testing graph data. This degradation primarily stems…

Cited by 0SourceScholar