Joschka Kersting, Gesa Benndorf · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28160 · open-access PDF
Programable Logic Controller (PLC) coding is a manual, IDE-centric task that requires constant context switching between documentation, project files, and code editors. Recent work has demonstrated that retrieval-augmented large language models can generate vendor-compliant Structured Text at high compilation rates \cite{pred}, yet these systems treat code generation as a one-shot pipeline: the engineer submits a query and receives code, without persistent knowledge of the specific plant. 我々はこのパラダイムを3つの方向で拡張する植物意識の会話コピオットを提示する。
Machine translation (Meta M2M100); the English original follows.
Programmable Logic Controller (PLC) coding remains a manual, IDE-centric task that demands constant context switching between documentation, project files, and code editors. Recent work has demonstrated that retrieval-augmented large language models can generate vendor-compliant Structured Text at high compilation rates \cite{pred}, yet these systems treat code generation as a one-shot pipeline: the engineer submits a query and receives code, with no persistent knowledge of the specific plant. We present a plant-aware conversational copilot that extends this paradigm in three directions: plant
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