A. Schwung

From Chain-of-Note to Explainable Cognitive Prompting: Reproducible Multi-Layer Validation for Auditable LLM-Assisted PLC Programming : Structured Explainability and Deterministic Reasoning for Industrial PLC Applications

Explainability in Large Language Model (LLM)–assisted PLC programming is essential for industrial adoption, where engineers must understand, validate, and maintain generated control logic under strict safety and standardization constraints. Existing explainability-oriented prompting approaches such as Chain of Note (Co...

Standard Conformant Prompting (SCP): A Reproducible Framework for Compiler-Ready PLC Code Generation with Large Language Models : From Post-Hoc Verification to Standard-Driven Code Synthesis in Industrial Automation

Generating PLC programs with Large Language Models (LLMs) that are directly deployable in industrial toolchains remains challenging because outputs must satisfy IEC 61131-3 semantics and vendor-specific compilation constraints. Verification-centric prompting such as Chain-of-Verification (CoVe) can reduce reasoning err...

Benchmarking and validation of prompting techniques for AI-assisted industrial PLC programming

Active learning for interactive prompt clarification in safety-critical programmable logic controller code generation

CoT+ (Chain-of-Thought Extended): A reproducible multi-reasoning prompting architecture for deterministic PLC code generation