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Same Query, Different Answer: Run-to-Run Variance in Semantic Query Processing

Paper recorded by Signals 4 on 2026-10-09 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-09 on arXiv · recorded by Signals 4 on 2026-10-12

Category: cs.AI · 人工智能 · first seen 2026-10-12

Abstract

Semantic query engines ask a large language model (LLM) to judge individual rows, and benchmarks compare these engines on the quality of a few executions at temperature 0. We measure how much another execution changes. We re-execute the text and tabular workloads of SemBench, LRO-Bench, and UDA-Bench through their own harnesses, log every one of 1.2 million model calls, and reanalyze SemBench's pu

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#350 most recent of 960 cs.AI papers we have recorded · ↑ newer: MC-EvoBench: Auditing Experience-Driven Self-Improvement in Minecraft · ↓ older: FORTE: A Production Framework for Feature Evaluation and Deprecation i
Cite this page: Same Query, Different Answer: Run-to-Run Variance in Semantic Query Processing: the #350 most recent of 960 cs.AI papers we have recorded (as of 2026-10-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/same-query-different-answer-run-to-run-variance-in-semantic-query-processing.html
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