collaborators

5 papers

cs.CY2026

Auditing Alignment Controllability in LLMs via Political Axes

Bartol Bućan, Nikola Sočec, Sarah Isufi +5

Political audits of large language models (LLMs) usually reduce each to one point on a political compass. But that resting point barely matters in deployment: a model must land som…

cs.AI2026

Large Language Models as Optimizers: A Survey of Direct vs. Tool-Augmented Approaches and Their Performance Frontiers

Roko Peran, Luka Hobor, Mihael Kovac +1

Large Language Models (LLMs) are increasingly involved in complex mathematical optimization, even if the pragmatic user who triggers them is unaware of it. After all, many real-wor…

cs.SE2026

AI-Assisted Unit Test Writing and Test-Driven Code Refactoring: A Case Study

Ema Smolic, Mario Brcic, Luka Hobor +1

Many software systems originate as prototypes or minimum viable products (MVPs), developed with an emphasis on delivery speed and responsiveness to changing requirements rather tha…

cs.AI2026

Bayesian Elicitation with LLMs: Model Size Helps, Extra "Reasoning" Doesn't Always

Luka Hobor, Mario Brcic, Mihael Kovac +1

Large language models (LLMs) have been proposed as alternatives to human experts for estimating unknown quantities with associated uncertainty, a process known as Bayesian elicitat…

cs.LG2026

Comparative Analysis of Modern Machine Learning Models for Retail Sales Forecasting

Luka Hobor, Mario Brcic, Lidija Polutnik +1

Accurate demand forecasting is critical for brick-and-mortar retailers to optimize inventory management and minimize costs. This study evaluates statistical baselines, tree-based e…