Issue
Dagstuhl Reports, Volume 15, Issue 11
-
Part of:
Volume:
Dagstuhl Reports, Volume 15
Journal: Dagstuhl Reports (DagRep)
Event
- Dagstuhl Seminars 25451, 25452, 25461, 25471, 25491, 25492
Publication Details
- published at: 2026-07-28
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Access Numbers
- Detailed Access Statistics available here
-
Total Accesses (updated on a weekly basis)
0Documents
Documents
No documents found matching your filter selection.
Document
Complete Issue
Dagstuhl Reports, Volume 15, Issue 11, November 2025, Complete Issue
Abstract
Dagstuhl Reports, Volume 15, Issue 11, November 2025, Complete Issue
Cite as
Dagstuhl Reports, Volume 15, Issue 11, pp. 1-180, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
Copy BibTex To Clipboard
@Article{DagRep.15.11,
title = {{Dagstuhl Reports, Volume 15, Issue 11, November 2025, Complete Issue}},
pages = {1--180},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {11},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.11},
URN = {urn:nbn:de:0030-drops-275003},
doi = {10.4230/DagRep.15.11},
annote = {Keywords: Dagstuhl Reports, Volume 15, Issue 11, November 2025, Complete Issue}
}
Document
Front Matter
Dagstuhl Reports, Table of Contents, Volume 15, Issue 11, 2025
Abstract
Dagstuhl Reports, Table of Contents, Volume 15, Issue 11, 2025
Cite as
Dagstuhl Reports, Volume 15, Issue 11, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
Copy BibTex To Clipboard
@Article{DagRep.15.11.i,
title = {{Dagstuhl Reports, Table of Contents, Volume 15, Issue 11, 2025}},
pages = {i--ii},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {11},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.11.i},
URN = {urn:nbn:de:0030-drops-274893},
doi = {10.4230/DagRep.15.11.i},
annote = {Keywords: Table of Contents, Frontmatter}
}
Document
Bayesian Optimisation (Dagstuhl Seminar 25451)
Abstract
This report documents the programme and outcomes of Dagstuhl Seminar 25451, "Bayesian Optimisation", held from November 2–7, 2025. The seminar brought together 39 international experts from machine learning, optimisation, statistics, and engineering to discuss recent advances, open challenges, and emerging research directions in Bayesian optimisation. The programme comprised plenary talks spanning foundational issues, benchmarking, and the growing interaction between Bayesian optimisation and generative AI, alongside focused working groups on key thematic areas. Beyond technical discussions, the seminar placed strong emphasis on community building and worked towards establishing best practices. This report summarises the plenary contributions, the outcomes of the working groups, and additional community-driven activities, including a collection of practical "tricks of the trade" and exploratory benchmarking exercises.
Cite as
Jürgen Branke, Frank Hutter, Giulia Pedrielli, Matthias Poloczek, and Leonard Papenmeier. Bayesian Optimisation (Dagstuhl Seminar 25451). In Dagstuhl Reports, Volume 15, Issue 11, pp. 1-66, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
Copy BibTex To Clipboard
@Article{branke_et_al:DagRep.15.11.1,
author = {Branke, J\"{u}rgen and Hutter, Frank and Pedrielli, Giulia and Poloczek, Matthias and Papenmeier, Leonard},
title = {{Bayesian Optimisation (Dagstuhl Seminar 25451)}},
pages = {1--66},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {11},
editor = {Branke, J\"{u}rgen and Hutter, Frank and Pedrielli, Giulia and Poloczek, Matthias and Papenmeier, Leonard},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.11.1},
URN = {urn:nbn:de:0030-drops-274940},
doi = {10.4230/DagRep.15.11.1},
annote = {Keywords: AutoML, Bayesian optimization, Benchmarking, Gaussian processes}
}
Document
A Roadmap Towards Practical Applications of Neurosymbolic Learning and Reasoning (Dagstuhl Seminar 25452)
Abstract
Neurosymbolic Artificial Intelligence (NeSy) promises to combine the scalability and adaptability of neural networks with the precision and interpretability of logic-based reasoning systems. Despite significant theoretical advances and growing interest in the field, the development of NeSy systems that seamlessly integrate symbolic and sub-symbolic elements at scale for real-world practical applications remains an open challenge. This Dagstuhl Seminar brought together leading researchers from diverse fields including machine learning, logic, knowledge representation, knowledge discovery, robotics, healthcare, and natural sciences to chart a roadmap for advancing NeSy systems from synthetic benchmarks to practical deployment. The seminar addressed four key challenges: (I) developing realistic benchmarks and standardized evaluation frameworks for NeSy systems, (II) identifying and advancing applications in robotics, healthcare, and scientific discovery, (III) creating open-source libraries to lower entry barriers and accelerate development, and (IV) creating accessible educational materials to broaden participation in the field. Through structured discussions, breakout sessions, and collaborative planning, participants developed concrete action plans and deliverables, including a planned Communications of the ACM article, open-source library development (ULLER, DeepLog), educational resources, and improvements to the field’s Wikipedia entry. This report documents the seminar’s presentations, discussions, and findings, and presents strategic recommendations for realizing the promise of Neurosymbolic AI in real-world applications.
Cite as
Thiviyan Thanapalasingam, Annette ten Teije, and Frank van Harmelen. A Roadmap Towards Practical Applications of Neurosymbolic Learning and Reasoning (Dagstuhl Seminar 25452). In Dagstuhl Reports, Volume 15, Issue 11, pp. 67-86, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
Copy BibTex To Clipboard
@Article{thanapalasingam_et_al:DagRep.15.11.67,
author = {Thanapalasingam, Thiviyan and Teije, Annette ten and van Harmelen, Frank},
title = {{A Roadmap Towards Practical Applications of Neurosymbolic Learning and Reasoning (Dagstuhl Seminar 25452)}},
pages = {67--86},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {11},
editor = {Thanapalasingam, Thiviyan and Teije, Annette ten 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.15.11.67},
URN = {urn:nbn:de:0030-drops-274934},
doi = {10.4230/DagRep.15.11.67},
annote = {Keywords: Neurosymbolic Artificial Intelligence, Machine Learning, Logic, Knowledge Representation \& Reasoning, Sub-symbolic \& Symbolic Integration}
}
Document
Security and Privacy of Large Language Models (Dagstuhl Seminar 25461)
Abstract
Large Language Models (LLMs) have rapidly evolved from experimental systems capable of generating simple text to powerful general-purpose tools that solve exam-level problems, assist human experts, summarize complex documents, and write code, leading to their widespread deployment in production environments to improve productivity. Their rapid adoption has outpaced scientific understanding of the associated security and privacy risks, creating a growing gap between real-world use and trust in LLM-based applications. Unlike traditional machine learning models, LLMs are inherently general-purpose, operate at unprecedented scale, are often proprietary, and are accessed through interactive dialog interfaces. This makes their behavior difficult to predict and introduces novel attack surfaces and emerging phenomena such as hallucinations. Existing methods and analyzes for conventional machine learning are insufficient to cope with these aspects. So, this Dagstuhl Seminar "Security and Privacy of Large Language Models" (25461) aimed to initiate a systematic scientific discussion on the security and privacy of language models by bringing together researchers from AI, security, privacy, and natural language processing to address three central questions: how safe and secure are LLMs in adversarial environments; to what extent users’ privacy may be at risk when interacting with LLMs; and what other categories of societal impact may arise from the rapid advancement of LLM technologies. The seminar sought to systematize existing knowledge, identify high-risk applications and prevalent attack vectors, discuss defense strategies and deployment challenges, and outline directions for future research in LLM security and privacy.
Cite as
Stephan Günnemann, Pavel Laskov, Emil Lupu, Vera Rimmer, Advije Rizvani, and Qianying Liao. Security and Privacy of Large Language Models (Dagstuhl Seminar 25461). In Dagstuhl Reports, Volume 15, Issue 11, pp. 87-113, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
Copy BibTex To Clipboard
@Article{gunnemann_et_al:DagRep.15.11.87,
author = {G\"{u}nnemann, Stephan and Laskov, Pavel and Lupu, Emil and Rimmer, Vera and Rizvani, Advije and Liao, Qianying},
title = {{Security and Privacy of Large Language Models (Dagstuhl Seminar 25461)}},
pages = {87--113},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {11},
editor = {G\"{u}nnemann, Stephan and Laskov, Pavel and Lupu, Emil and Rimmer, Vera and Rizvani, Advije and Liao, Qianying},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.11.87},
URN = {urn:nbn:de:0030-drops-274951},
doi = {10.4230/DagRep.15.11.87},
annote = {Keywords: Large Language Models, Artifician Intelligence, Security and Privacy}
}
Document
Online Algorithms beyond Competitive Analysis (Dagstuhl Seminar 25471)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 25471: "Online Algorithms beyond Competitive Analysis". This seminar brought 45 leading researchers in online algorithms and related areas together for a discussion of the recent progress and challenges in various aspects of online algorithms. The seminar included several talks of varying lengths and an open problem session. In addition, sufficient time was set aside for research discussions and collaborations.
Cite as
Sungjin Im, Nicole Megow, Debmalya Panigrahi, Sahil Singla, and Golnoosh Shahkarami. Online Algorithms beyond Competitive Analysis (Dagstuhl Seminar 25471). In Dagstuhl Reports, Volume 15, Issue 11, pp. 114-133, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
Copy BibTex To Clipboard
@Article{im_et_al:DagRep.15.11.114,
author = {Im, Sungjin and Megow, Nicole and Panigrahi, Debmalya and Singla, Sahil and Shahkarami, Golnoosh},
title = {{Online Algorithms beyond Competitive Analysis (Dagstuhl Seminar 25471)}},
pages = {114--133},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {11},
editor = {Im, Sungjin and Megow, Nicole and Panigrahi, Debmalya and Singla, Sahil and Shahkarami, Golnoosh},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.11.114},
URN = {urn:nbn:de:0030-drops-274926},
doi = {10.4230/DagRep.15.11.114},
annote = {Keywords: algorithms under uncertainty, beyond worst-case algorithm design, online algorithms}
}
Document
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 25491)
Abstract
The Dagstuhl Seminar "Approaches and Applications of Inductive Programming" (AAIP) took place in 2025 for the seventh time. The focus of this seminar series is methods and applications of learning computer programs from incomplete and informal specifications such as input/output examples or natural language prompts. Researchers come from different areas, mostly from machine learning and other branches of artificial intelligence research, cognitive scientists interested in human learning in complex domains, and researchers with a background in formal methods and programming languages. The focus of the AAIP 2025 seminar was the application of large language models to code generation and the evaluation of quality of generated code in comparison with other, classic inductive programming approaches. Furthermore, neuro-symbolic approaches to inductive programming, were explored. Applications of inductive programming in different domains such as biomedical scientific discovery, control code generation in complex industrial settings, and programming education were discussed.
Cite as
Ute Schmid, Gust Verbruggen, and Sonja Niemann. Approaches and Applications of Inductive Programming (Dagstuhl Seminar 25491). In Dagstuhl Reports, Volume 15, Issue 11, pp. 134-156, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
Copy BibTex To Clipboard
@Article{schmid_et_al:DagRep.15.11.134,
author = {Schmid, Ute and Verbruggen, Gust and Niemann, Sonja},
title = {{Approaches and Applications of Inductive Programming (Dagstuhl Seminar 25491)}},
pages = {134--156},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {11},
editor = {Schmid, Ute and Verbruggen, Gust and Niemann, Sonja},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.11.134},
URN = {urn:nbn:de:0030-drops-274912},
doi = {10.4230/DagRep.15.11.134},
annote = {Keywords: Diffusion Models, Inductive Programming, LLMs, Program Synthesis, Programming by Examples}
}
Document
Generalized Voronoi Diagrams and Applications (Dagstuhl Seminar 25492)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 25492 "Generalized Voronoi Diagrams and Applications", which was held from 30 November to 5 December 2025. The seminar brought together 28 scientists working on various aspects of generalized Voronoi diagrams such as efficient diagram computation, fitting diagrams to observed cell systems or using Voronoi diagrams to model material microstructure. The report contains the abstracts of the tutorials and presentations held during the seminar. It also contains a summary of the discussion sessions that were organized in smaller break-out groups.
Cite as
Andreas Alpers, David P. Bourne, Henning F. Poulsen, and Claudia Redenbach. Generalized Voronoi Diagrams and Applications (Dagstuhl Seminar 25492). In Dagstuhl Reports, Volume 15, Issue 11, pp. 157-178, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)
Copy BibTex To Clipboard
@Article{alpers_et_al:DagRep.15.11.157,
author = {Alpers, Andreas and Bourne, David P. and Poulsen, Henning F. and Redenbach, Claudia},
title = {{Generalized Voronoi Diagrams and Applications (Dagstuhl Seminar 25492)}},
pages = {157--178},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2026},
volume = {15},
number = {11},
editor = {Alpers, Andreas and Bourne, David P. and Poulsen, Henning F. and Redenbach, Claudia},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.11.157},
URN = {urn:nbn:de:0030-drops-274908},
doi = {10.4230/DagRep.15.11.157},
annote = {Keywords: Laguerre tessellation, generalized balanced power diagram, anisotropic Voronoi diagram, cellular materials, grains, polycrystals}
}