Parametric Editorial Generation for Competitive Programming: A Human-in-the-Loop Working Prototype

Theodor Moroianu, Adrian Marius Dumitran, Tamio-Vesa Nakajima, Adrian Miclăuş, Ştefan-Cosmin Dăscălescu, Mihai-Alexandru Vasiluţă, Laura Marin
Proceedings of the Impactful and Responsible AI Systems for Education Workshop, PMLR 339:187-193, 2026.

Abstract

We present EditoriaLLM, a web application that uses large language models to generate competitive programming editorials from problem statements, reference solutions, algorithmic tags, audience settings, and style templates. This approach streamlines using a general-purpose chat interface into a simple, all-in-one tool, tailored to our particular use-case. EditoriaLLM is designed as a human-in-the-loop assistant for competitive programming education, with early adoption already observed in national competition contexts.

Cite this Paper

BibTeX
@InProceedings{pmlr-v339-moroianu26a, title = {Parametric Editorial Generation for Competitive Programming: A Human-in-the-Loop Working Prototype}, author = {Moroianu, Theodor and Dumitran, Adrian Marius and Nakajima, Tamio-Vesa and Micl\u{a}u\c{s}, Adrian and D\u{a}sc\u{a}lescu, \c{S}tefan-Cosmin and Vasilu\c{t}\u{a}, Mihai-Alexandru and Marin, Laura}, booktitle = {Proceedings of the Impactful and Responsible AI Systems for Education Workshop}, pages = {187--193}, year = {2026}, editor = {Basu Mallick, Debshila and Woodhead, Simon and Wang, Zichao and Ananda, Muktha and Burstein, Jill and Murphy, April}, volume = {339}, series = {Proceedings of Machine Learning Research}, month = {28 Jun}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v339/main/assets/moroianu26a/moroianu26a.pdf}, url = {https://proceedings.mlr.press/v339/moroianu26a.html}, abstract = {We present EditoriaLLM, a web application that uses large language models to generate competitive programming editorials from problem statements, reference solutions, algorithmic tags, audience settings, and style templates. This approach streamlines using a general-purpose chat interface into a simple, all-in-one tool, tailored to our particular use-case. EditoriaLLM is designed as a human-in-the-loop assistant for competitive programming education, with early adoption already observed in national competition contexts.} }
Endnote
%0 Conference Paper %T Parametric Editorial Generation for Competitive Programming: A Human-in-the-Loop Working Prototype %A Theodor Moroianu %A Adrian Marius Dumitran %A Tamio-Vesa Nakajima %A Adrian Miclăuş %A Ştefan-Cosmin Dăscălescu %A Mihai-Alexandru Vasiluţă %A Laura Marin %B Proceedings of the Impactful and Responsible AI Systems for Education Workshop %C Proceedings of Machine Learning Research %D 2026 %E Debshila Basu Mallick %E Simon Woodhead %E Zichao Wang %E Muktha Ananda %E Jill Burstein %E April Murphy %F pmlr-v339-moroianu26a %I PMLR %P 187--193 %U https://proceedings.mlr.press/v339/moroianu26a.html %V 339 %X We present EditoriaLLM, a web application that uses large language models to generate competitive programming editorials from problem statements, reference solutions, algorithmic tags, audience settings, and style templates. This approach streamlines using a general-purpose chat interface into a simple, all-in-one tool, tailored to our particular use-case. EditoriaLLM is designed as a human-in-the-loop assistant for competitive programming education, with early adoption already observed in national competition contexts.
APA
Moroianu, T., Dumitran, A.M., Nakajima, T., Miclăuş, A., Dăscălescu, Ş., Vasiluţă, M. & Marin, L.. (2026). Parametric Editorial Generation for Competitive Programming: A Human-in-the-Loop Working Prototype. Proceedings of the Impactful and Responsible AI Systems for Education Workshop, in Proceedings of Machine Learning Research 339:187-193 Available from https://proceedings.mlr.press/v339/moroianu26a.html.

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