output
20082025
most citedNavigating Compiler Errors with AI Assistance -- A Study of GPT Hints in an Introductory Programming Course

19 citations

33 papers

math.AG2025

Grassmann cactus variety and socle dimension

Weronika Buczyńska, Jarosław Buczyński, Maciej Gałązka

Grassmann cactus variety is a common generalisation of Grassmann secant variety and cactus variety. In their definitions one considers the vector spaces of fixed dimension that are…

nlin.CD2025★ 5 cited

Selectivity filter conductance, rectification and fluctuations of subdomains - how can this all relate to the value of Hurst exponent in the dwell-times of ion channels states?

Przemysław Borys, Paulina Trybek, Beata Dworakowska +4

The Hurst effect in the signals describing ion channels' activity has been known for many years. This effect is present in the experimental recordings of single-channel currents, b…

cs.CE2025

Competitive algorithms for calculating the ground state properties of Bose-Fermi mixtures

Tomasz Świsłocki, Krzysztof Gawryluk, Mirosław Brewczyk +1

In this work we define, analyze, and compare different numerical schemes that can be used to study the ground state properties of Bose-Fermi systems, such as mixtures of different…

cs.PL2024★ 2 cited

Comparison of Three Programming Error Measures for Explaining Variability in CS1 Grades

Valdemar Švábenský, Maciej Pankiewicz, Jiayi Zhang +3

Programming courses can be challenging for first year university students, especially for those without prior coding experience. Students initially struggle with code syntax, but a…

cs.SE2024★ 19 cited

Navigating Compiler Errors with AI Assistance -- A Study of GPT Hints in an Introductory Programming Course

Maciej Pankiewicz, Ryan S. Baker

We examined the efficacy of AI-assisted learning in an introductory programming course at the university level by using a GPT-4 model to generate personalized hints for compiler er…

eess.IV2024★ 7 cited

Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classification

Oleksandr Fedoruk, Konrad Klimaszewski, Aleksander Ogonowski +1

The availability of training data is one of the main limitations in deep learning applications for medical imaging. Data augmentation is a popular approach to overcome this problem…