Structuring and Tokenizing Distributed User Interest Context for Generative Recommendation

Ruizhong Qiu, Yinglong Xia, Dongqi Fu, Hanqing Zeng, Ren Chen et al.|June 18, 2026arXiv

Key Takeaway

Combining graph-based user co-engagement patterns with semantic tokenization creates more accurate user interest representations for generative recommendation systems at scale.

Summary

This paper presents G2Rec, a framework that improves generative recommendation systems by better organizing user behavior and item information. It combines graph-based user interaction patterns with semantic tokenization to help recommendation models understand what users want next, without needing labeled user interests.

applications architecture data

Key Terms

generative-recommendation item-tokenization user-interest-context semantic-tokenization