GenRec: A Preference-Oriented Generative Framework for Large-Scale Recommendation

arXiv:2604.14878v1 Announce Type: cross Abstract: Generative Retrieval (GR) offers a promising paradigm for recommendation through next-token prediction (NTP). However, scaling it to large-scale industrial systems introduces three challenges: (i) within a single request, the identical model inputs may produce inconsistent outputs due to the pagination request mechanism; (ii) the prohibitive cost of encoding long user behavior sequences with multi-token item representations based on semantic IDs,