Delft (the Netherlands), April 13-15, 2026
Website: https://icgi2026.tudelft.nl
Contact: icgi26@easychair.org

Grammatical Inference is the research area at the intersection of Machine Learning and Formal Language Theory. Since 1993, the International Conference on Grammatical Inference (ICGI) is the meeting place for presenting, discovering, and discussing the latest research results on the foundations of learning languages, from theoretical and algorithmic perspectives to their applications (natural language or document processing, bioinformatics, model checking and software verification, program synthesis, robotic planning and control, intrusion detection…).

This 17th edition of ICGI will be held in Delft, the Netherlands.


## Types of contributions

We welcome three types of papers:

- Formal and/or technical papers describe original contributions (theoretical, emperical, or conceptual) in the field of grammatical inference. A technical paper should clearly describe the situation or problem tackled, the relevant state of the art, the position or solution suggested, and the benefits of the contribution.
- Position papers can describe completely new research positions, approaches, or open problems. Current limits can be discussed. In all cases, rigor in the presentation will be required. Such papers must describe precisely the situation, problem, or challenge addressed, and demonstrate how current methods, tools, or ways of reasoning, may be inadequate.
- Tool papers describing a new tool for grammatical inference. The tool must be publicly available and the paper has to contain several use-case studies describing the use of the tool. In addition, the paper should clearly describe the implemented algorithms, input parameters and syntax, and the produced output.


## Topics of interest

Typical topics of interest include (but are not limited to):

- Theoretical aspects of grammatical inference: learning paradigms, learnability results, the complexity of learning.
- Learning algorithms for language classes inside and outside the Chomsky hierarchy. Learning tree grammars, graph grammars, ….
- Learning probability distributions over strings, trees or graphs, or transductions thereof.
- Research on query learning, active learning, and other interactive learning paradigms.
- Research on methods using or including, but not limited to, spectral learning, state-merging, distributional learning, statistical relational learning, statistical inference, or Bayesian learning
- Theoretical analysis of computational models, such as artificial neural networks, automata, grammars, Markov models, and their expressiveness through the lens of formal languages and inference.
- Experimental and theoretical analysis of different approaches to grammatical inference, including artificial neural networks, statistical methods, symbolic methods, information-theoretic approaches, minimum description length, complexity-theoretic approaches, heuristic methods, etc.
- Leveraging formal language tools, models, and theory to improve the explainability, interpretability, or verifiability of neural networks or other black box models.
- Learning with contextualized data: for instance, Grammatical Inference from strings or trees paired with semantic representations, or learning by situated agents and robots.
- Successful applications of grammatical inference to other areas, including, but not limited to, natural language processing, computational linguistics, model checking, software verification, bioinformatics, robotic planning and control, and pattern recognition.


## Guidelines for authors

Accepted papers will be published within the Proceedings of Machine Learning Research series (http://proceedings.mlr.press/). Submission instructions can be found on the conference website. The total length of the paper should not exceed 12 pages on A4-size paper (references and appendix may exceed this limit but be warned that reviewers may not read after page 12). We strongly encourage to use the JMLR style file for LaTeX (https://ctan.org/tex-archive/macros/latex/contrib/jmlr); this is required for the final published version.

The peer review process is double-blind: we expect submitted papers to be anonymous.


## Timeline (all dates are Anywhere on Earth)

- The deadline for submissions is: December 17, 2025
- Notification of acceptance: February 2, 2026
- Conference: April 13-15, 2026


## ICGI Steering Committee

Johanna Björklund (Umeå University)
Jeffrey Heinz (Stony Brook University)
Adam Jardine (Rutgers University)
Franz Mayr (Universidad ORT Uruguay)
Joshua Moerman (Open Universiteit)
Guillaume Rabusseau (Montreal University & Mila)
Chihiro Shibata (Hosei University)
Lena Strobl (Umeå University)
Ryo Yoshinaka (Tohoku University)


## Local Organisers

Sicco Verwer (TU Delft)
Joshua Moerman (Open Universiteit)