Issue
Dagstuhl Reports, Volume 15, Issue 7
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Part of:
Volume:
Dagstuhl Reports, Volume 15
Journal: Dagstuhl Reports (DagRep)
Event
- Dagstuhl Seminars 25281, 25282, 25291, 25292, 25301, 25302, 25311, 25312
Publication Details
- published at: 2026-04-30
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
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Document
Complete Issue
Dagstuhl Reports, Volume 15, Issue 7, July 2025, Complete Issue
Abstract
Dagstuhl Reports, Volume 15, Issue 7, July 2025, Complete Issue
Cite as
Dagstuhl Reports, Volume 15, Issue 7, pp. 1-304, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
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@Article{DagRep.15.7,
title = {{Dagstuhl Reports, Volume 15, Issue 7, July 2025, Complete Issue}},
pages = {1--304},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {7},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.7},
URN = {urn:nbn:de:0030-drops-257703},
doi = {10.4230/DagRep.15.7},
annote = {Keywords: Dagstuhl Reports, Volume 15, Issue 7, July 2025, Complete Issue}
}
Document
Front Matter
Dagstuhl Reports, Table of Contents, Volume 15, Issue 7, 2025
Abstract
Dagstuhl Reports, Table of Contents, Volume 15, Issue 7, 2025
Cite as
Dagstuhl Reports, Volume 15, Issue 7, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
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@Article{DagRep.15.7.i,
title = {{Dagstuhl Reports, Table of Contents, Volume 15, Issue 7, 2025}},
pages = {i--ii},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {7},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.7.i},
URN = {urn:nbn:de:0030-drops-257617},
doi = {10.4230/DagRep.15.7.i},
annote = {Keywords: Table of Contents, Frontmatter}
}
Document
From Sparse Interpolation to Signal Processing: New Synergies (Dagstuhl Seminar 25281)
Abstract
In a data-rich digital world, finding sparse, efficient representations - especially for multi-exponential models - has become critical, particularly when measurements are costly or noisy. These models, which involve complex or real exponents, underpin key processes in signal processing, relaxation dynamics, chemical reactions, heat transfer, and fluid dynamics, with widespread real-world impact. The challenge lies at the intersection of several computational disciplines: structured matrices, rational approximation, sparse interpolation, quadrature, tensor decompositions, and subdivision methods - each offering potential pathways to more robust and efficient algorithms. Multi-exponential analysis is foundational across engineering and industry, enabling advances in DOA estimation, remote sensing, MRI, superresolution, seismology, radio astronomy, and telecommunications - areas vital to energy, health, transportation, and space research. This Dagstuhl Seminar "From Sparse Interpolation to Signal Processing: New Synergies" (25281) brought together experts from computational harmonic analysis, numerical linear algebra, computer algebra, signal processing, approximation theory, and engineering applications to foster cross-disciplinary collaboration and accelerate innovation in this dynamic field.
Cite as
Annie Cuyt, Dirk de Villiers, Wen-shin Lee, Ana C. Matos, Gerlind Plonka-Hoch, and Ramonika Sengupta. From Sparse Interpolation to Signal Processing: New Synergies (Dagstuhl Seminar 25281). In Dagstuhl Reports, Volume 15, Issue 7, pp. 1-21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
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@Article{cuyt_et_al:DagRep.15.7.1,
author = {Cuyt, Annie and de Villiers, Dirk and Lee, Wen-shin and Matos, Ana C. and Plonka-Hoch, Gerlind and Sengupta, Ramonika},
title = {{From Sparse Interpolation to Signal Processing: New Synergies (Dagstuhl Seminar 25281)}},
pages = {1--21},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {7},
editor = {Cuyt, Annie and de Villiers, Dirk and Lee, Wen-shin and Matos, Ana C. and Plonka-Hoch, Gerlind and Sengupta, Ramonika},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.7.1},
URN = {urn:nbn:de:0030-drops-257690},
doi = {10.4230/DagRep.15.7.1},
annote = {Keywords: exponential analysis, structured matrices, quadrature, subdivision, computer algebra, applications}
}
Document
Theory of Neural Language Models (Dagstuhl Seminar 25282)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 25282 "Theory of Neural Language Models". The seminar aimed to bring researchers together to lay a foundation for continued work on the theory of neural language models, focusing on questions including: How do transformers, RNNs, other NLMs, and their variants, compare with one another in expressivity and trainability? How do the successes and failures of NLMs predicted by theoretical models manifest in practice? What modifications, or what wholly new architectures, are suggested by the theory?
Cite as
Pablo Barcelo, David Chiang, George Cybenko, Lena Strobl, and Andy Yang. Theory of Neural Language Models (Dagstuhl Seminar 25282). In Dagstuhl Reports, Volume 15, Issue 7, pp. 22-52, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
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@Article{barcelo_et_al:DagRep.15.7.22,
author = {Barcelo, Pablo and Chiang, David and Cybenko, George and Strobl, Lena and Yang, Andy},
title = {{Theory of Neural Language Models (Dagstuhl Seminar 25282)}},
pages = {22--52},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {7},
editor = {Barcelo, Pablo and Chiang, David and Cybenko, George and Strobl, Lena and Yang, Andy},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.7.22},
URN = {urn:nbn:de:0030-drops-257689},
doi = {10.4230/DagRep.15.7.22},
annote = {Keywords: Dagstuhl Seminar, Neural Networks, Language Models, Automata, Logic, Model Theory, Circuit Complexity}
}
Document
(Actual) Neurosymbolic AI: Combining Deep Learning and Knowledge Graphs (Dagstuhl Seminar 25291)
Abstract
In the past decade, both deep learning (DL) and knowledge graphs (KGs) have seen astonishing growth and groundbreaking milestones – DL due to newly available resources (e.g., accessibility of (modern) web scale data), previously un-scalable techniques (e.g., transformers), and modern hardware; KGs due to successful standardization, web-scale integration, and previously un-scalable techniques for querying and inference. This has brought new and increased interest to both fields, and especially in how they can complement each other. % This report documents the program and the outcomes of Dagstuhl Seminar 25291 "(Actual) Neurosymbolic AI: Combining Deep Learning and Knowledge Graphs". This Dagstuhl Seminar brought 34 internationally recognized experts together to examine the gap between deep learning and knowledge graphs, and architect their integration: neurosymbolic AI.
Cite as
Pascal Hitzler, Cogan Shimizu, Daria Stepanova, and Frank van Harmelen. (Actual) Neurosymbolic AI: Combining Deep Learning and Knowledge Graphs (Dagstuhl Seminar 25291). In Dagstuhl Reports, Volume 15, Issue 7, pp. 53-123, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
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@Article{hitzler_et_al:DagRep.15.7.53,
author = {Hitzler, Pascal and Shimizu, Cogan and Stepanova, Daria and van Harmelen, Frank},
title = {{(Actual) Neurosymbolic AI: Combining Deep Learning and Knowledge Graphs (Dagstuhl Seminar 25291)}},
pages = {53--123},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {7},
editor = {Hitzler, Pascal and Shimizu, Cogan and Stepanova, Daria and van Harmelen, Frank},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.7.53},
URN = {urn:nbn:de:0030-drops-257675},
doi = {10.4230/DagRep.15.7.53},
annote = {Keywords: deep learning, knowledge graphs, neurosymbolic ai}
}
Document
New Frontiers in AI for Game Design (Dagstuhl Seminar 25292)
Abstract
Game design has often influenced, and been influenced by, computer science research. In recent decades researchers and designers have sought to bring these two fields even closer together: to find new ways to think about the game design process; new ways to drive innovation in computer science through playful exploration; and ultimately find new ways to play, design and think about games through computational lenses. AI is impacting the creative industries in more ways than ever before, some welcome, others less so. It is important to find ways for both researchers and practitioners to come together to map out possible futures for this space, to understand where research can contribute, what it can learn from game design in return, and how we can enrich the creative practice of everyone involved.
This report covers Dagstuhl Seminar 25292: New Frontiers for AI in Game Design. It outlines the motivations for organising the seminar, summarises many of the working groups that took place, and disseminates some of the games, theories and other materials created during the seminar. The report offers theoretical frameworks, working prototypes and exploratory discussions that present many possible futures for both the creative practice of game design, and the academic field of games research. None of these futures are singularly correct, and many more remain out there to be found; this document merely charts out some possible paths into the unknown that we found exciting to consider.
Cite as
M Charity, Michael Cook, and Nicolaas Vas. New Frontiers in AI for Game Design (Dagstuhl Seminar 25292). In Dagstuhl Reports, Volume 15, Issue 7, pp. 124-186, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
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@Article{charity_et_al:DagRep.15.7.124,
author = {Charity, M and Cook, Michael and Vas, Nicolaas},
title = {{New Frontiers in AI for Game Design (Dagstuhl Seminar 25292)}},
pages = {124--186},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {7},
editor = {Charity, M and Cook, Michael and Vas, Nicolaas},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.7.124},
URN = {urn:nbn:de:0030-drops-257667},
doi = {10.4230/DagRep.15.7.124},
annote = {Keywords: artificial intelligence, Computational Creativity, Game Design, Human-Centred Computing, Procedural Content Generation}
}
Document
Linguistics and Language Models: What Can They Learn from Each Other? (Dagstuhl Seminar 25301)
Abstract
An international group of 40 scholars in computational linguistics, natural language processing, and cognitive science was assembled to discuss the relationship between linguistics and contemporary language models. Over the course of the week, presentations and work sessions grappled with questions about how LMs can support linguistic research (either as a source of evidence, or as a tool); how linguistic knowledge can inform the design, interpretation, or application of LMs; and what framing is appropriate for the language functionality of LMs.
Cite as
Anna Rogers, Nathan Schneider, Bonnie Webber, A. Seza Doğruöz, and Asad Sayeed. Linguistics and Language Models: What Can They Learn from Each Other? (Dagstuhl Seminar 25301). In Dagstuhl Reports, Volume 15, Issue 7, pp. 187-212, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
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@Article{rogers_et_al:DagRep.15.7.187,
author = {Rogers, Anna and Schneider, Nathan and Webber, Bonnie and Do\u{g}ru\"{o}z, A. Seza and Sayeed, Asad},
title = {{Linguistics and Language Models: What Can They Learn from Each Other? (Dagstuhl Seminar 25301)}},
pages = {187--212},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {7},
editor = {Rogers, Anna and Schneider, Nathan and Webber, Bonnie and Do\u{g}ru\"{o}z, A. Seza and Sayeed, Asad},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.7.187},
URN = {urn:nbn:de:0030-drops-257652},
doi = {10.4230/DagRep.15.7.187},
annote = {Keywords: cognitive modelling, language models, linguistic theory}
}
Document
NatureHCI: Towards Designing Computer-Enriched Nature Experiences (Dagstuhl Seminar 25302)
Abstract
This report documents the proceedings and outcomes of a NatureHCI seminar, in which 21 researchers and academics from across the world gathered at Schloss Dagstuhl, Germany, to discuss the grand challenges that this field currently faces. We present the activities developed day by day, including PechaKucha self-introductions, collaborative workshops, hands-on design sessions, and group discussions. Finally, we present the pathways that attendees proposed to start addressing the seminar’s critical question: how interactive technologies can be designed responsibly to improve our experience of nature, thereby strengthening our connection with nature, which benefits health and wellbeing? Ultimately, with this report, we hope to inspire upcoming Dagstuhl Seminar proposals interested in advancing the field of HCI.
Cite as
Masahiko Inami, Michael Jones, Zhuying Li, Florian `Floyd' Mueller, and Maria F. Montoya. NatureHCI: Towards Designing Computer-Enriched Nature Experiences (Dagstuhl Seminar 25302). In Dagstuhl Reports, Volume 15, Issue 7, pp. 213-252, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
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@Article{inami_et_al:DagRep.15.7.213,
author = {Inami, Masahiko and Jones, Michael and Li, Zhuying and Mueller, Florian `Floyd' and Montoya, Maria F.},
title = {{NatureHCI: Towards Designing Computer-Enriched Nature Experiences (Dagstuhl Seminar 25302)}},
pages = {213--252},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {7},
editor = {Inami, Masahiko and Jones, Michael and Li, Zhuying and Mueller, Florian `Floyd' and Montoya, Maria F.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.7.213},
URN = {urn:nbn:de:0030-drops-257645},
doi = {10.4230/DagRep.15.7.213},
annote = {Keywords: NatureHCI, Nature Interactions, Wilderness, Technology, Wellbeing, Sustainability, More-Than-Human, Human-Computer Interaction, non-humans, animals, nature}
}
Document
Generative AI in Programming Education (Dagstuhl Seminar 25311)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 25311 "Generative AI in Programming Education". During the seminar, we examined the transformative impact of Generative AI on programming education. Because they can solve many introductory tasks given only natural language prompts, AI tools are challenging established approaches to programming education, in which there has been a traditional emphasis on writing small programs and providing (automated) feedback to learners. While these developments raise concerns about student over-reliance and inaccurate feedback, they also open opportunities for new pedagogical practices, such as fostering prompt literacy, adapting curricula, and designing AI-assisted learning tools. The present seminar convened 42 international experts to exchange knowledge, present research, and share innovations through keynotes, lightning talks, and tool demonstrations. Collaborative working groups explored implications for learning outcomes, assessment, equity, human values, and tool design, while identifying directions for systematic evaluation and interdisciplinary research. The seminar successfully established a foundation for a sustained community of practice and set an agenda for advancing programming education in the era of Generative AI.
Cite as
Michelle Craig, Paul Denny, Natalie Kiesler, and James Prather. Generative AI in Programming Education (Dagstuhl Seminar 25311). In Dagstuhl Reports, Volume 15, Issue 7, pp. 253-279, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
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@Article{craig_et_al:DagRep.15.7.253,
author = {Craig, Michelle and Denny, Paul and Kiesler, Natalie and Prather, James},
title = {{Generative AI in Programming Education (Dagstuhl Seminar 25311)}},
pages = {253--279},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {7},
editor = {Craig, Michelle and Denny, Paul and Kiesler, Natalie and Prather, James},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.7.253},
URN = {urn:nbn:de:0030-drops-257636},
doi = {10.4230/DagRep.15.7.253},
annote = {Keywords: artificial intelligence, computer programming, computing education, generative ai, large language models}
}
Document
Building Privacy-Preserving Technologies of Societal Impact (Dagstuhl Seminar 25312)
Abstract
This report describes the motivation, purpose, and scope of Dagstuhl Seminar 25312 "Building Privacy-Preserving Technologies of Societal Impact" as well as documents its program and outcomes. This inter-disciplinary seminar brought together computer science researchers and practitioners working on building privacy-enhancing technologies - most notably secure computation applications - and researchers in expertise in other relevant disciplines including law, medicine, and social studies. Besides the applied nature of the seminar that capitalized on the participants' desire to facilitate adoption of privacy-enhancing techniques in real world applications, a unique aspect of this seminar was the shared passion of the participants to use their expertise to build tools for protecting vulnerable populations and for other public good purposes.
Cite as
Marina Blanton and Liina Kamm. Building Privacy-Preserving Technologies of Societal Impact (Dagstuhl Seminar 25312). In Dagstuhl Reports, Volume 15, Issue 7, pp. 280-302, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
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@Article{blanton_et_al:DagRep.15.7.280,
author = {Blanton, Marina and Kamm, Liina},
title = {{Building Privacy-Preserving Technologies of Societal Impact (Dagstuhl Seminar 25312)}},
pages = {280--302},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {7},
editor = {Blanton, Marina and Kamm, Liina},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.7.280},
URN = {urn:nbn:de:0030-drops-257629},
doi = {10.4230/DagRep.15.7.280},
annote = {Keywords: Privacy-enhancing technologies, applications, societal impact, secure computation}
}