Merge and Branch: Efficient Tree-Structured Supervised Fine-Tuning of LLMs for Recommendation.

arXiv:2610.37973v1 Announce Type: cross Abstract: LLM-based generative recommendation reads long, text-rich interaction histories but generates only short semantic identifiers (SIDs). This asymmetry makes supervised fine-tuning inefficient: encoding the histor