A 2026 preprint asks whether recommendation explanations deserve evaluation beyond ranking accuracy

The preprint is titled Beyond Ranking Accuracy: Evaluating LLM-Cited Feature Rationales for Next Basket Repurchase Recommendation and is identified by arXiv ID 2608.30333.

The record lists eight authors: Yanan Cao, Anay Dombe, Murali Mohana Krishna Dandu, Shreeranjani Srirangamsridharan, Sinduja Subramaniam, Yogananth Mahalingam, Evren Korpeoglu, and Kannan Achan.

It was published in 2026 in the arXiv cs.AI Daily Feed and is marked preprint, so it is not peer-reviewed evidence.

The supplied evidence contains bibliographic metadata only; no abstract, methods, results, quotations, or PDF were retained.

Recommendation teams often assess whether a product was selected, but the paper’s title signals a separate question: whether an LLM-generated rationale identifies features that genuinely support a next-basket repurchase recommendation