The UNLP workshop focuses on advances in Ukrainian Natural Language Processing. The aim of the workshop is to bring together leading academics, researchers, and practitioners in the fields of Natural Language Processing and Computational Linguistics who work with the Ukrainian language or do cross-Slavic research that can be applied to the Ukrainian language.


The Second UNLP will be will be held online in conjunction with the 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023).


Registration for UNLP 2023: TBD

Note: The workshop is free of charge for the attendees from Ukraine to encourage Ukrainian researchers to attend and submit papers to the workshop.


The workshop invites submissions presenting computational approaches, applications, models, and resources for the Ukrainian language or cross-Slavic research. See Call for Papers and Shared Task for more information.


The workshop will provide Grammarly Premium to all authors. To request Grammarly Premium, please submit this form.

Important dates

December 23, 2022 — First call for workshop papers

January 9, 2023 — Second call for workshop papers

February 13, 2023 — Workshop paper due

March 13, 2023 — Notification of acceptance

March 27, 2023 — Camera-ready papers due

May 5 or 6, 2023 — Workshop dates

We stand in solidarity with Ukraine


UNLP condemns the Russian invasion of Ukraine and the barbaric war that the Russian Federation leads against the Ukrainian people. We stand in solidarity with the people of Ukraine during these trying times.

Code of Ethics

UNLP honors the ethical code set out in the ACL Code of Ethics. We kindly ask the authors to consider the ethical impact of their research, use of data, and potential applications of their work. Where a paper may raise ethical issues, we ask that the authors include in the paper an explicit discussion of these issues. We reserve the right to reject papers on ethical grounds, where the authors are judged to have operated counter to the code of ethics, or have inadequately addressed legitimate ethical concerns with their work.

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