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News/Merge and Branch: Efficient Tree-Structured Supervised Fine-Tuning of LLMs for Recommendation
arxiv
PublishedOctober 31, 2026 at 4:00 AM

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

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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 history is expensive, yet each history usually

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