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            <title>Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology</title>
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    <abstract>Explanatory dialogue systems serve as intuitive interface between non-expert users and explainable AI (XAI) systems. The interaction with these kind of systems benefits especially from the integration of structured domain knowledge, e.g., by means of bipolar argumentation trees. So far, these domain-specific structures need to be created manually, therewith impairing the flexibility of the system with respect to the domain. We address this limitation by adapting an existing pipeline for topic-independent acquisition of argumentation trees in the field of persuasive, argumentative dialogue to the area of explanatory dialogue. This shift is achieved by a) introducing and investigating different formulations of auxiliary claims per feature of the explanation of the AI model, b) exploring the influence of pre-grouping of the arguments with respect to the feature they address, c) suggesting adaptions to the existing algorithm of the pipeline for obtaining a tree structure, and d) utilizing a new approach for determining the type of the relationship between the arguments. Through a step-wise expert evaluation for the domain titanic survival, we identify the best performing variant of our pipeline. With this variant we conduct a user study comparing the automatically generated argumentation trees against their manually created counterpart in the domains titanic survival and credit acquisition. This assessment of the suitability of the generated argumentation trees for a later integration into dialogue-based XAI systems as domain knowledge yields promising results.</abstract>
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%0 Conference Proceedings
%T Automatic Generation of Structured Domain Knowledge for Dialogue-based XAI Systems
%A Schindler, Carolin
%A Feustel, Isabel
%A Rach, Niklas
%A Minker, Wolfgang
%Y Torres, Maria Ines
%Y Matsuda, Yuki
%Y Callejas, Zoraida
%Y del Pozo, Arantza
%Y D’Haro, Luis Fernando
%S Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology
%D 2025
%8 May
%I Association for Computational Linguistics
%C Bilbao, Spain
%@ 979-8-89176-248-0
%F schindler-etal-2025-automatic
%X Explanatory dialogue systems serve as intuitive interface between non-expert users and explainable AI (XAI) systems. The interaction with these kind of systems benefits especially from the integration of structured domain knowledge, e.g., by means of bipolar argumentation trees. So far, these domain-specific structures need to be created manually, therewith impairing the flexibility of the system with respect to the domain. We address this limitation by adapting an existing pipeline for topic-independent acquisition of argumentation trees in the field of persuasive, argumentative dialogue to the area of explanatory dialogue. This shift is achieved by a) introducing and investigating different formulations of auxiliary claims per feature of the explanation of the AI model, b) exploring the influence of pre-grouping of the arguments with respect to the feature they address, c) suggesting adaptions to the existing algorithm of the pipeline for obtaining a tree structure, and d) utilizing a new approach for determining the type of the relationship between the arguments. Through a step-wise expert evaluation for the domain titanic survival, we identify the best performing variant of our pipeline. With this variant we conduct a user study comparing the automatically generated argumentation trees against their manually created counterpart in the domains titanic survival and credit acquisition. This assessment of the suitability of the generated argumentation trees for a later integration into dialogue-based XAI systems as domain knowledge yields promising results.
%U https://aclanthology.org/2025.iwsds-1.1/
%P 1-11

Markdown (Informal)

[Automatic Generation of Structured Domain Knowledge for Dialogue-based XAI Systems](https://aclanthology.org/2025.iwsds-1.1/) (Schindler et al., IWSDS 2025)

• Automatic Generation of Structured Domain Knowledge for Dialogue-based XAI Systems (Schindler et al., IWSDS 2025)

ACL

• Carolin Schindler, Isabel Feustel, Niklas Rach, and Wolfgang Minker. 2025. Automatic Generation of Structured Domain Knowledge for Dialogue-based XAI Systems. In Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology, pages 1–11, Bilbao, Spain. Association for Computational Linguistics.