Hendrik Buschmeier

Hendrik Buschmeier

hbuschme@uni-bielefeld.de
Institution: Bielefeld University
Department: Digital Linguistics Lab, Faculty of Linguistics and Literary Studies
Position: Tenure-track Professor of Digital Linguistics
https://dililab.uni-bielefeld.de/
Solving difficulties in understanding in human-robot interaction (due to knowledge gaps or vagueness and ambiguity inherent to verbal communication) is a key issue, which – if not properly addressed by building on human interactional mechanisms – risks the success of the interaction because instructing the robot in useful ways may well be impossible and/or lead to non-acceptance of the technology by human users.

Dialogue, Interaction, Conversational Agents, Multimodality, Computational Linguistics

Repair, feedback and adaptation; Politeness; Reference; Perspective-taking

  • Desirability of Proactive Robots: A User Study on Spoken Interaction Initiation (2026)

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    Published at: Hri 2026 Proceedings of the 21st ACM IEEE International Conference on Human Robot Interaction
    DOI: 10.1145/3757279.3785558

  • Forms of understanding for XAI-Explanations (2025)

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    Published at: Cognitive Systems Research (Volume: 94)
    DOI: 10.1016/j.cogsys.2025.101419

  • A BFO-Based Ontological Analysis of Entities in Social XAI (2025)

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    Published at: Frontiers in Artificial Intelligence and Applications (Volume: 409)
    DOI: 10.3233/FAIA250498

  • Insights for Proactive Agents: Design Considerations, Challenges, and Recommendations (2025)

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    Published at: Ceur Workshop Proceedings (Volume: 3957)

  • Embodied Conversational Systems in Human–Robot Interaction: Introduction to the Special Issue (2025)

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    Published at: Dialogue and Discourse (Volume: 16)
    DOI: 10.5210/dad.2025.301

  • Are Multimodal Large Language Models Pragmatically Competent Listeners in Simple Reference Resolution Tasks? (2025)

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    Published at: Proceedings of the Annual Meeting of the Association for Computational Linguistics
    DOI: 10.18653/v1/2025.findings-acl.1236

  • Conversation analysis and conversational technologies: Finding the common ground between academia and industry (2024)

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    Published at: Discourse and Communication (Volume: 18)
    DOI: 10.1177/17504813241267118

  • Can AI explain AI? Interactive co-construction of explanations among human and artificial agents (2024)

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    Published at: Discourse and Communication (Volume: 18)
    DOI: 10.1177/17504813241267069

  • Quote to Explain: Using Multimodal Metalinguistic Markers to Explain Large Language Models' Understanding Capabilities (2024)

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    Published at: ACM International Conference Proceeding Series
    DOI: 10.1145/3686215.3689203

  • Multimodal Co-Construction of Explanations with XAI Workshop (2024)

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    Published at: ACM International Conference Proceeding Series
    DOI: 10.1145/3678957.3689205