Author

A. M. Ebrahimi

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#artificial intelligence Preprint Aug 2026

LLM Post-Training as Brownfield Maintenance: An Industrial Perspective on Dataware Engineering

From an industrial code-generation improvement effort, a maintainer's perspective on why this work is hard in practice is offered, distilling three recurring challenges, zero-sum mixture design, yield as the binding metric, and end-to-end integration under uncertainty, and arguing that progress depends less on one-off recipes than on an engineering discipline for programming dataware.

Gopi Krishnan Rajbahadur, A. M. Ebrahimi, Boyuan Chen et al. · 0 citations

Jul 2026

To Add Is Machine, To Delete Is Human: Measuring and Mitigating Deletion Avoidance in LLM Code Editing

Teaching deletion during post-training reduces deletion avoidance and improves broader code-editing performance, suggesting the behavior is undertrained rather than beyond reach.

A. M. Ebrahimi, M. M. Hasan, Aaditya Bhatia et al. · arXiv.org · 0 citations