Hailong Shi

HiST: Hierarchical Semantic Tree Augmentation for Generative Recommendation

This work proposes HiST (Hierarchical Semantic Tree Augmentation), a novel framework that leverages branch information to bridge the semantic gap and can be effectively integrated with various existing tokenization methods to enhance recommendation model performance.

Instance-Level Consistent Graph With Unsupervised Human Parts for Person Re-Identification

HiST: Hierarchical Semantic Tree Augmentation for Generative Recommendation

Recommendation systems are indispensable for helping users navigate the vast product catalogs of modern online platforms. Recently, generative recommendation has emerged as a promising paradigm due to its unified and flexible formulation, and it has been adopted in various commercial scenarios. However, we find that di...