AI RESEARCH
Revisiting Quantum Code Generation: Where Should Domain Knowledge Live?
arXiv CS.LG
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ArXi:2603.22184v1 Announce Type: new Recent advances in large language models (LLMs) have enabled the automation of an increasing number of programming tasks, including code generation for scientific and engineering domains. In rapidly evolving software ecosystems such as quantum software development, where frameworks expose complex abstractions, a central question is how best to incorporate domain knowledge into LLM-based assistants while preserving maintainability as libraries evolve.