Xiaowen Sun

Xiaowen Sun

she/her

Ph.D

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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.

Pages

Posts

Blog Post number 4

less than 1 minute read

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Blog Post number 3

less than 1 minute read

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

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Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Teaching

portfolio

publications

Learning Visually Grounded Human-Robot Dialog in a Hybrid Neural Architecture

Published in 31st International Conference on Artificial Neural Networks (ICANN 2022), 2022

Keywords: Human-Robot Interaction, Visual Dialog Generation, Natural Language Processing, Computer Vision, and Recurrent Neural Networks

Recommended citation: Sun, X. W., Weber, C., Kerzel, M., Weber, T., Li, M. D., Wermter, S. (2022). Learning Visually Grounded Human-Robot Dialog in a Hybrid Neural Architecture. In: Pimenidis, E., Angelov, P., Jayne, C., Papaleonidas, A., Aydin, M. (eds) Artificial Neural Networks and Machine Learning – ICANN 2022. ICANN 2022. Lecture Notes in Computer Science, vol 13530. Springer, Cham. https://doi.org/10.1007/978-3-031-15931-2_22.
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Details Make a Difference: Object State-Sensitive Neurorobotic Task Planning

Published in 33rd International Conference on Artificial Neural Networks (ICANN 2024), 2024

Keywords: Object State Identification, Robotic Task Planning, Large Language Models, and Multimodality

Recommended citation: Sun, X. W., Zhao, X. F., Lee, J. H., Lu, W. H., Kerzel, M., & Wermter, S. (2024). Details make a difference: Object state-sensitive neurorobotic task planning. 33rd International Conference on Artificial Neural Networks (ICANN), pp. 261–275.
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A Framework for Adapting Human-Robot Interaction to Diverse User Groups

Published in International Conference on Social Robotics (ICSR 2024), 2024

Keywords: Social Robotics, Symbolic Planning, Age Recognition, Large Language Models, and Human-Robot Interaction

Recommended citation: Pekarek Rosin, T. et al. (2025). A Framework for Adapting Human-Robot Interaction to Diverse User Groups. In: Palinko, O., et al. Social Robotics. ICSR + AI 2024. Lecture Notes in Computer Science(), vol 15563. Springer, Singapore. https://doi.org/10.1007/978-981-96-3525-2_3
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Uncertainty, Vagueness, and Ambiguity in Human-Robot Interaction: Why Conceptualization Matters

Published in 2nd Interactive AI for Human-Centered Robotics Workshop at HRI, 2026

Keywords: Human-Robot Interaction, Embodied Agents, Uncertainty, Vagueness, and Ambiguity,

Recommended citation: Sun, X. W., Weber, C., Kerzel, M., Josua, S., & Wermter, S. (2026). Uncertainty, Vagueness, and Ambiguity in Human-Robot Interaction: Why Conceptualization Matters. Interactive AI for Human-Centered Robotics Workshop at Human-Robot Interaction 2026.
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[Ph.D Thesis] Active Clarification in Human-Robot Interaction via Object State Perception and Reasoning

Published in Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky (SUB Hamburg), 2026

Keywords: Embodied Agents, Human-Robot Interaction, Ambiguity, Object State Perception, Active Clarification, and Artificial Intelligence

Recommended citation: Sun, X. W. “Active clarification in human-robot interaction via object state perception and reasoning,” Ph.D. dissertation, Universität Hamburg, Hamburg, Germany, 2026. [Online]. Available: https://ediss.sub.uni-hamburg.de/handle/ediss/12538.
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[Preprint] StateVLM: A State-Aware Vision-Language Model for Robotic Affordance Reasoning

Published in arXiv preprint arXiv:2605.03927, 2026

Keywords: Vision-Language Models, Referring Expression Comprehension, Visual Perception, Object-State Understanding, and Affordance Reasoning

Recommended citation: Sun, X. W., Kerzel, M., Li, M. D., Zhao, X. F, Striker, P., & Wermter, S. (2026). StateVLM: A State-Aware Vision-Language Model for Robotic Affordance Reasoning. arXiv preprint arXiv:2605.03927.
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