Access Paths for Efficient Ordering with Large Language Models
Quick summary
arXiv:2509.00303v4 Announce Type: replace-cross Abstract: In this work, we present the \texttt{LLM ORDER BY} semantic operator as a logical abstraction and conduct a systematic study of its physical implementations. First, we propose several improvements to existing semantic sorting algorithms and introduce a semantic-aware external merge sort algorithm. Our extensive evaluation reveals that no single implementation offers universal optimality on all datasets. From our evaluations, we observe a general scaling relationship between sorting cost and the ordering quality for comparison-based algo
Key takeaways
- arXiv:2509.00303v4 Announce Type: replace-cross Abstract: In this work, we present the \texttt{LLM ORDER BY} semantic operator as a logical abstraction and conduct a systematic study of its physical implementations.
- First, we propose several improvements to existing semantic sorting algorithms and introduce a semantic-aware external merge sort algorithm.
- Our extensive evaluation reveals that no single implementation offers universal optimality on all datasets.
Why it matters
“Access Paths for Efficient Ordering with Large Language Models” highlights the need for repeatable measurement rather than a single impressive demonstration. Independent validation across datasets and clearly stated limitations determine whether a result can guide product decisions.
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