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    <abstract>This study compares explanation-augmented knowledge distillation with few-shot in-context learning for LLM-based exam question classification. Fine-tuned smaller language models achieved competitive performance with greater consistency than large mode few-shot approaches, which exhibited notable variability across different examples. Hyperparameter selection proved essential, with extremely low learning rates significantly impairing model performance.</abstract>
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%0 Conference Proceedings
%T Addressing Few-Shot LLM Classification Instability Through Explanation-Augmented Distillation
%A Muntean, William
%A Betts, Joe
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress
%D 2025
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-218-84229-1
%F muntean-betts-2025-addressing
%X This study compares explanation-augmented knowledge distillation with few-shot in-context learning for LLM-based exam question classification. Fine-tuned smaller language models achieved competitive performance with greater consistency than large mode few-shot approaches, which exhibited notable variability across different examples. Hyperparameter selection proved essential, with extremely low learning rates significantly impairing model performance.
%U https://aclanthology.org/2025.aimecon-wip.24/
%P 197-203

Markdown (Informal)

[Addressing Few-Shot LLM Classification Instability Through Explanation-Augmented Distillation](https://aclanthology.org/2025.aimecon-wip.24/) (Muntean & Betts, AIME-Con 2025)

• Addressing Few-Shot LLM Classification Instability Through Explanation-Augmented Distillation (Muntean & Betts, AIME-Con 2025)

ACL

• William Muntean and Joe Betts. 2025. Addressing Few-Shot LLM Classification Instability Through Explanation-Augmented Distillation. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Works in Progress, pages 197–203, Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).