{"id":313,"date":"2026-02-25T13:45:00","date_gmt":"2026-02-25T12:45:00","guid":{"rendered":"https:\/\/grammarlearning.org\/?p=313"},"modified":"2026-02-25T13:33:49","modified_gmt":"2026-02-25T12:33:49","slug":"icgi-2026-postponed-new-cfp-and-dates","status":"publish","type":"post","link":"https:\/\/grammarlearning.org\/fr\/icgi-2026-postponed-new-cfp-and-dates\/","title":{"rendered":"ICGI 2026 postponed; New CFP and dates!"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Call for papers: ICGI 2026, 17th International Conference on Grammatical Inference<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Delft (the Netherlands), <strong>NEW DATES: October 26-28, 2026<\/strong><br>Website:&nbsp;<a href=\"https:\/\/icgi2026.tudelft.nl\/\">https:\/\/icgi2026.tudelft.nl<\/a><br>Contact:&nbsp;<a href=\"mailto:icgi26@easychair.org\">icgi26@easychair.org<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Grammatical Inference<\/em>&nbsp;is the research area at the intersection of&nbsp;<em>Machine Learning<\/em>&nbsp;and&nbsp;<em>Formal Language Theory<\/em>. Since 1993, the International Conference on Grammatical Inference (ICGI) is the meeting place for presenting, discovering, and discussing the latest research results on the&nbsp;<em>foundations of learning languages<\/em>, 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\u2026).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This 17th edition of ICGI will be held in Delft, the Netherlands.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Types of contributions<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">We welcome three types of papers:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><b>Regular papers<\/b> describe original contributions (theoretical, empirical, conceptual, or a software tool) in the field of grammatical inference. They 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.<\/li>\n\n\n\n<li><b>Extended abstract of published works<\/b> can be submitted to present already published work. Existing tools or applications of grammatical inference can also be presented in this track.<\/li>\n\n\n\n<li><b>WIP papers:<\/b> We also invite abstracts on work in progress. This allows you to present unfinished ideas that may be of interest to the grammatical inference community.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Only the regular papers will be published in the proceedings. The extended abstracts of published work and WIP papers will receive a light review process.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Topics of interest<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Typical topics of interest include (but are not limited to):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Theoretical aspects of grammatical inference: learning paradigms, learnability results, the complexity of learning.<\/li>\n\n\n\n<li>Learning algorithms for language classes inside and outside the Chomsky hierarchy. Learning tree grammars, graph grammars, \u2026.<\/li>\n\n\n\n<li>Learning probability distributions over strings, trees or graphs, or transductions thereof.<\/li>\n\n\n\n<li>Research on query learning, active learning, and other interactive learning paradigms.<\/li>\n\n\n\n<li>Research on methods using or including, but not limited to, spectral learning, state-merging, distributional learning, statistical relational learning, statistical inference, or Bayesian learning<\/li>\n\n\n\n<li>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.<\/li>\n\n\n\n<li>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.<\/li>\n\n\n\n<li>Leveraging formal language tools, models, and theory to improve the explainability, interpretability, or verifiability of neural networks or other black box models.<\/li>\n\n\n\n<li>Learning with contextualized data: for instance, Grammatical Inference from strings or trees paired with semantic representations, or learning by situated agents and robots.<\/li>\n\n\n\n<li>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.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Guidelines for authors<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Accepted regular papers will be published within the Proceedings of Machine Learning Research series (<a href=\"http:\/\/proceedings.mlr.press\/\">http:\/\/proceedings.mlr.press\/<\/a>). 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 (<a href=\"https:\/\/ctan.org\/tex-archive\/macros\/latex\/contrib\/jmlr\">https:\/\/ctan.org\/tex-archive\/macros\/latex\/contrib\/jmlr<\/a>); this is required for the final published version.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The peer review process is double-blind: we expect submitted papers to be anonymous.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Timeline (all dates are Anywhere on Earth)<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The submission deadline is: <strong>May 29, 2026<\/strong><\/li>\n\n\n\n<li>Notification of acceptance: July 10, 2026<\/li>\n\n\n\n<li>Conference: October 26-28, 2026<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">ICGI Steering Committee<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Johanna Bj\u00f6rklund (Umea\u030a University); Jeffrey Heinz (Stony Brook University); Adam Jardine (Rutgers University); Franz Mayr (Universidad ORT Uruguay); Joshua Moerman (Open Universiteit); Guillaume Rabusseau (Montreal University &amp; Mila); Chihiro Shibata (Hosei University); Lena Strobl (Umea\u030a University); Ryo Yoshinaka (Tohoku University)<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Local Organisers<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Sicco Verwer (TU Delft); Joshua Moerman (Open Universiteit)<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Program Committee<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Adam Jardine; Alexander Clark; Andrea Pferscher; Benedikt Bollig; Bernhard Aichernig; Chihiro Shibata; Dakotah Lambert; Falk Howar; Fran\u00e7ois Coste; Johanna Bj\u00f6rklund; Karl Meinke; Matthias Gall\u00e9; Maude Lizaire; Ryan Cotterell; R\u00e9mi Eyraud; Sergio Yovine; Steffen van Bergerem; Tiago Ferreira; More TBA\u2026<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Call for papers: ICGI 2026, 17th International Conference on Grammatical Inference Delft (the Netherlands), NEW DATES: October 26-28, 2026Website:&nbsp;https:\/\/icgi2026.tudelft.nlContact:&nbsp;icgi26@easychair.org Grammatical Inference&nbsp;is the research area at the intersection of&nbsp;Machine Learning&nbsp;and&nbsp;Formal Language Theory. Since 1993, the International Conference on Grammatical Inference (ICGI) is the meeting place for presenting, discovering, and discussing the\u2026<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/grammarlearning.org\/fr\/icgi-2026-postponed-new-cfp-and-dates\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":2080,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_members_access_role":[],"_members_access_error":""},"categories":[1],"tags":[],"class_list":["post-313","post","type-post","status-publish","format-standard","hentry","category-news"],"_links":{"self":[{"href":"https:\/\/grammarlearning.org\/fr\/wp-json\/wp\/v2\/posts\/313","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/grammarlearning.org\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/grammarlearning.org\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/grammarlearning.org\/fr\/wp-json\/wp\/v2\/users\/2080"}],"replies":[{"embeddable":true,"href":"https:\/\/grammarlearning.org\/fr\/wp-json\/wp\/v2\/comments?post=313"}],"version-history":[{"count":3,"href":"https:\/\/grammarlearning.org\/fr\/wp-json\/wp\/v2\/posts\/313\/revisions"}],"predecessor-version":[{"id":317,"href":"https:\/\/grammarlearning.org\/fr\/wp-json\/wp\/v2\/posts\/313\/revisions\/317"}],"wp:attachment":[{"href":"https:\/\/grammarlearning.org\/fr\/wp-json\/wp\/v2\/media?parent=313"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/grammarlearning.org\/fr\/wp-json\/wp\/v2\/categories?post=313"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/grammarlearning.org\/fr\/wp-json\/wp\/v2\/tags?post=313"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}