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Institute for Software and Systems Engineering
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Achieving 90% accuracy in fault localization while providing interpretable explanations could revolutionize root cause analysis in automotive systems.
Coordinated multi-LLM reasoning boosts fault classification accuracy in automotive systems, achieving a remarkable 0.917 Top-1 accuracy while enhancing interpretability.
Small LLMs can achieve the same fault diagnosis accuracy as larger models, challenging the assumption that bigger is always better in automotive software validation.
