RQ1's contrast is still unclaimed by its nearest neighbours¶

# research(2026-09). Checked on their abstract pages: Kumar, Lones, Maarek and Zantout, "Fine-Tuning Models for Automated Code Review Feedback" (arXiv:2605.12610, May 2026), fine-tune Code Llama on feedback distilled from a proprietary model, for student Java code. Begolli, Aksoy and Neider, "Fine-Tuning Multilingual Language Models for Code Review: An Empirical Study on Industrial C# Projects" (arXiv:2507.19271), pool public benchmarks with industrial repositories into one training corpus. Neither trains per project or per organization, and neither evaluates an adapter on another organization's data. The matched-against-mismatched contrast RQ1 registers, which asks whether an adaptation is specific to the organization it came from rather than to the task, does not appear in either.