Find Before You Fine-Tune: A Diagnostic Study of Small LLMs for Cybersecurity QA
Large Language Models (LLMs) are increasingly fine-tuned for critical-domain Question-Answering (QA), yet choosing which small model to adapt, before paying the cost of adaptation, remains difficult. Fine-tuning can improve domain alignment, but it may also erode prior knowledge, weaken instruction-following, or increase hallucination, especially when labeled data are scarce or rapidly evolving as in cybersecurity. We present FiT (Find before Fine-Tune), a task-oriented diagnostic framework that
Record details
Published: 21 July 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Healthcare
Retrieved: 22 July 2026
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ethics.ai (21 July 2026), “Find Before You Fine-Tune: A Diagnostic Study of Small LLMs for Cybersecurity QA,” evidence record 12350, https://ethics.ai/record/12350 (originally published by arXiv).
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