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Documents authored by Glotin, Maxence

Document
DOI: 10.4230/OASIcs.DX.2025.2
Are Diagnostic Concepts Within the Reach of LLMs?

Authors: Anna Sztyber-Betley, Elodie Chanthery, Louise Travé-Massuyès, Silke Merkelbach, Karol Kukla, Maxence Glotin, Alexander Diedrich, and Oliver Niggemann

Published in: OASIcs, Volume 136, 36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025)

Abstract
Model-based diagnosis is a cornerstone of system health monitoring, allowing for the identification of faulty components based on observed behavior and a formal system model. However, obtaining a useful and reliable model is often an expensive and manual task. While the generation of a formal model was the aim of previous work, in this paper, we propose a methodology to use large language models to generate Minimal Structurally Overdetermined sets (MSOs). MSOs are specific subsets of the model equations from which diagnosis tests can be obtained. We investigate two different directions: (i) the large-language-models' ability to generate MSO sets for hybrid systems, similar to those generated by the well-known Fault Diagnosis Toolbox (FDT) (ii) the automated generation of MSOs for Boolean circuits, as well as the computation of the diagnoses. We thus show how both dynamic and static systems can be analysed by large-language models and how their output can be used for effective fault diagnosis. We evaluate our approach on a set of arithmetic and logic circuits, using OpenAI’s LLMs 4o-mini, o1, and o3-mini.
Cite as

Anna Sztyber-Betley, Elodie Chanthery, Louise Travé-Massuyès, Silke Merkelbach, Karol Kukla, Maxence Glotin, Alexander Diedrich, and Oliver Niggemann. Are Diagnostic Concepts Within the Reach of LLMs?. In 36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025). Open Access Series in Informatics (OASIcs), Volume 136, pp. 2:1-2:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{sztyberbetley_et_al:OASIcs.DX.2025.2,
  author =	{Sztyber-Betley, Anna and Chanthery, Elodie and Trav\'{e}-Massuy\`{e}s, Louise and Merkelbach, Silke and Kukla, Karol and Glotin, Maxence and Diedrich, Alexander and Niggemann, Oliver},
  title =	{{Are Diagnostic Concepts Within the Reach of LLMs?}},
  booktitle =	{36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025)},
  pages =	{2:1--2:20},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-394-2},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{136},
  editor =	{Quinones-Grueiro, Marcos and Biswas, Gautam and Pill, Ingo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2025.2},
  URN =		{urn:nbn:de:0030-drops-247913},
  doi =		{10.4230/OASIcs.DX.2025.2},
  annote =	{Keywords: Fault Diagnosis, Large Language Models, LLMs, Model Based Diagnosis, MSO, Redundancy Relations, Conflicts, Diagnoses}
}
Document
DOI: 10.4230/OASIcs.DX.2024.13
MSO Sets and MTES for Dummies

Authors: Maxence Glotin, Louise Travé-Massuyès, and Elodie Chanthery

Published in: OASIcs, Volume 125, 35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024)

Abstract
Structural analysis-based diagnosis allows for the extraction of a wealth of information and properties by studying a structural model that represents a physical system. This diagnosis approach is centered on structurally overdetermined sets, which enable the generation of residuals for fault detection and isolation. As the 'for Dummies' editorial collection, this article aims at taking on complex concepts and making them easy to understand. It aims to clarify and compare key concepts in structural analysis, focusing on Minimally Structurally Overdetermined (MSO) sets and Minimal Test Equation Supports (MTES). Additionally, we explain and illustrate the Dulmage-Mendelsohn decomposition, which helps identify structurally overdetermined parts of the system and plays a important role in the structural analysis process. Through detailed exploration and practical examples, we demonstrate the roles, applications, and interrelations of these sets, highlighting their respective strengths and limitations. The paper provides an overview of the algorithms used to identify and use these sets, including a theoretical and practical comparison of their computational efficiency and diagnostic capabilities.
Cite as

Maxence Glotin, Louise Travé-Massuyès, and Elodie Chanthery. MSO Sets and MTES for Dummies. In 35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024). Open Access Series in Informatics (OASIcs), Volume 125, pp. 13:1-13:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{glotin_et_al:OASIcs.DX.2024.13,
  author =	{Glotin, Maxence and Trav\'{e}-Massuy\`{e}s, Louise and Chanthery, Elodie},
  title =	{{MSO Sets and MTES for Dummies}},
  booktitle =	{35th International Conference on Principles of Diagnosis and Resilient Systems (DX 2024)},
  pages =	{13:1--13:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-356-0},
  ISSN =	{2190-6807},
  year =	{2024},
  volume =	{125},
  editor =	{Pill, Ingo and Natan, Avraham and Wotawa, Franz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2024.13},
  URN =		{urn:nbn:de:0030-drops-221054},
  doi =		{10.4230/OASIcs.DX.2024.13},
  annote =	{Keywords: Structural analysis, MTES, MSO sets}
}
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