HyperPocket: Generative Point Cloud Completion. - Przemyslaw Spurek; Artur Kasymov; Marcin Mazur; Diana Janik; Slawomir Konrad Tadeja; Lukasz Struski; Jacek Tabor; Tomasz Trzcinski (IROS, 2022)

Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models. - Mohammadreza Banaei; Klaudia Balazy; Artur Kasymov; Rémi Lebret; Jacek Tabor; Karl Aberer (EACL (Findings), 2023)

HyperNeRFGAN: Hypernetwork approach to 3D NeRF GAN. - Adam Kania; Artur Kasymov; Maciej Zieba; Przemyslaw Spurek (CoRR, 2023)

AutoLoRA: AutoGuidance Meets Low-Rank Adaptation for Diffusion Models. - Artur Kasymov; Marcin Sendera; Michal Stypulkowski; Maciej Zieba; Przemyslaw Spurek (CoRR, 2024)

MultiPlaneNeRF: Neural radiance field with non-trainable representation. - Dominik Zimny; Artur Kasymov; Adam Kania; Jacek Tabor; Maciej Zieba; Marcin Mazur; Przemyslaw Spurek (Expert Syst. Appl., 2025)

NegGS: Negative Gaussian Splatting. - Artur Kasymov; Bartosz Czekaj; Marcin Mazur; Jacek Tabor; Przemyslaw Spurek (Inf. Sci., 2025)

Classifier-free Guidance with Adaptive Scaling. - Dawid Malarz; Artur Kasymov; Maciej Zieba; Jacek Tabor; Przemyslaw Spurek (CoRR, 2025)

PALATE: Peculiar Application of the Law of Total Expectation to Enhance the Evaluation of Deep Generative Models. - Tadeusz Dziarmaga; Marcin Kadziolka; Artur Kasymov; Marcin Mazur (CoRR, 2025)

UnGuide: Learning to Forget with LoRA-Guided Diffusion Models. - Agnieszka Polowczyk; Alicja Polowczyk; Dawid Malarz; Artur Kasymov; Marcin Mazur; Jacek Tabor; Przemyslaw Spurek (CoRR, 2025)

A Framework for Large-Scale Synthetic Graph Dataset Generation. - Sajad Darabi; Piotr Bigaj; Dawid Majchrowski; Artur Kasymov; Pawel M. Morkisz; Alex Fit-Florea (IEEE Trans. Neural Networks Learn. Syst., 2025)