M. Martinc

A Large-Scale Instruction-Tuning Dataset and Models for Slovenian Vision-Language Tasks

Assessing Readability with LLMs: The Role of Reasoning and Few-Shot Prompting

A systematic benchmark of diverse open-source LLMs for multilingual readability assessment is conducted, focusing on the prediction of discrete readability levels required by educational frameworks, to establish the viability of out-of-the-box LLMs as robust, cross-lingual readability assessors.

Navigating the digital spectrum: Assessing political bias, stability, and downstream fairness in Large Language Models

A robust Political Compass Test evaluation framework is introduced that samples 300 configurations across an eight-dimensional perturbation space varying language, framing, instructions, answer format, option order, and persona wording, and results show most models lean Libertarian-Left on average and larger models sho...

A Domain-Targeted Question-Answering Dataset for Food and Nutrition Applications

Evaluation of four general-purpose LLMs on FoodBench tasks shows limited performance across nutrient estimation, traffic-light classification, and food interoperability, even with few-shot prompting, highlighting the need for domain-specialized LLMs fine-tuned on food data.