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arXiv · 2606.01145

Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches

Teddy Ferdinan·Bartłomiej Koptyra·Mikołaj Langner·Tomasz Adamczyk·Łukasz Radliński·Maciej Markiewicz·Aleksander Szczęsny·Stanisław Woźniak·Tymoteusz Romanowicz·Dzmitry Pihulski·Mateusz Zbrocki·Mateusz Śmigielski·Michał Rajkowski·Mateusz Biedka·Konrad Kiełczyński·Konrad Wojtasik·Jacek Duszenko·Jan Eliasz·Piotr Matys·Michał Bernacki-Janson·Maria Bellaniar Ismiati·Latius Hermawan·Wiktoria Mieleszczenko-Kowszewicz·Anna Kubicka-Sowińska·Grzegorz Chodak·Karol Postawa·Paweł Zyblewski·Tomasz Szandała·Łukasz Sterczewski·Adrian Chajec·Paweł Niewiadomski·Piotr Gruber·Marcin Wdowikowski·Sławomir Czarnecki·Bartłomiej Kryszak·Dominik Drabik·Tomasz Kajdanowicz·Kamil Mamak·Paweł Preś·Katarzyna Paczkowska·Joachim Sobczuk·Tomasz Zięba·Jan Kocoń·Maciej Piasecki·Przemysław Kazienko
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Abstract

While Reasoning Language Models (RLMs) are rapidly emerging as powerful tools for scientific research, their impact is primarily concentrated in "hard science" fields. The slow -- or lack of -- adoption of RLMs in other branches of science is causing a widening gap in research productivity. In this survey, we provide the first comprehensive analysis of RLM adoption across 28 scientific disciplines following the classification used by the European Research Council (ERC), spanning the Social Sciences and Humanities, Physical Sciences and Engineering, and Life Sciences. We examine how RLMs are developed, evaluated, and applied across disciplines. Furthermore, we introduce a maturity-oriented assessment framework based on available domain-specific development and evaluation resources, revealing substantial disparities in RLM maturity that become even more pronounced when only publicly available resources are considered. Finally, we highlight current implementation paradigms that are gaining popularity across disciplines, current challenges, and future directions in enabling RLM adoption across science.

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Teddy Ferdinan, Bartłomiej Koptyra, Mikołaj Langner, Tomasz Adamczyk, Łukasz Radliński, Maciej Markiewicz, Aleksander Szczęsny, Stanisław Woźniak, Tymoteusz Romanowicz, Dzmitry Pihulski, Mateusz Zbrocki, Mateusz Śmigielski, Michał Rajkowski, Mateusz Biedka, Konrad Kiełczyński, Konrad Wojtasik, Jacek Duszenko, Jan Eliasz, Piotr Matys, Michał Bernacki-Janson, Maria Bellaniar Ismiati, Latius Hermawan, Wiktoria Mieleszczenko-Kowszewicz, Anna Kubicka-Sowińska, Grzegorz Chodak, Karol Postawa, Paweł Zyblewski, Tomasz Szandała, Łukasz Sterczewski, Adrian Chajec, Paweł Niewiadomski, Piotr Gruber, Marcin Wdowikowski, Sławomir Czarnecki, Bartłomiej Kryszak, Dominik Drabik, Tomasz Kajdanowicz, Kamil Mamak, Paweł Preś, Katarzyna Paczkowska, Joachim Sobczuk, Tomasz Zięba, Jan Kocoń, Maciej Piasecki, Przemysław Kazienko. 2026-05-31. Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches. https://arxiv.org/abs/2606.01145

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