G2Rec: Structuring and Tokenizing Distributed User Interest Context for Generative Recommendation

arXiv·medium signal

A Meta-affiliated team (Qiu, Xia, Fu, Zeng et al.) introduces G2Rec, which unifies holistic graph-based user co-engagement modeling with semantic tokenization for industrial-scale generative recommendation, capturing interest patterns without ground-truth interest labels. The paper reports online deployment across production surfaces plus public-dataset experiments showing gains over prior generative-rec and graph-tokenization baselines. Practitioner relevance: it addresses the scalability ceiling of graph methods and the heuristic, unsupervised nature of semantic tokenization that block real recsys deployments.