arxiv
PublishedOctober 15, 2026 at 4:00 AM
A, B, C, or Stable? Accuracy and Order Sensitivity Diverge in LLM Multiple-Choice Evaluation
Publisher summary· verbatim
arXiv:2608.11947v2 Announce Type: replace-cross Abstract: Multiple-choice question (MCQ) benchmarks are widely used to evaluate large language models, yet a single reported accuracy number is not enough to distinguish a model's latent ability from order sensitivity. Debiasing methods tend to be judg
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivA Theoretical Analysis of Test-Driven Code Generation14harxivScalable Adaptation of 3D Geometric Foundation Models via Weak Supervision from Internet Video14harxivCan Graph Learning Learn Circuits?14harxivBeyond Fixed Acquisition Functions: Temporal Difference Active Learning for Perturbation Discovery14hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗