42 citations · 42 across the 6 of their papers we have counts for
12 papers · 1 filter
Navigating the digital spectrum: Assessing political bias, stability, and downstream fairness in Large Language Models
Luka Debevc, Nishan Chatterjee, Antoine Doucet +2
Large Language Models are increasingly deployed as information intermediaries, yet measuring their political behavior remains fragile because questionnaire results mix model dispos…
FoodSEM: Large Language Model Specialized in Food Named-Entity Linking
Ana Gjorgjevikj, Matej Martinc, Gjorgjina Cenikj +3
This paper introduces FoodSEM, a state-of-the-art fine-tuned open-source large language model (LLM) for named-entity linking (NEL) to food-related ontologies. To the best of our kn…
SEKE: Specialised Experts for Keyword Extraction
Matej Martinc, Hanh Thi Hong Tran, Senja Pollak +1
Keyword extraction involves identifying the most descriptive words in a document, allowing automatic categorisation and summarisation of large quantities of diverse textual data. R…
Multi-Task Learning for Features Extraction in Financial Annual Reports
Syrielle Montariol, Matej Martinc, Andraž Pelicon +4
For assessing various performance indicators of companies, the focus is shifting from strictly financial (quantitative) publicly disclosed information to qualitative (textual) info…
Tracking Semantic Change in Slovene: A Novel Dataset and Optimal Transport-Based Distance
Marko Pranjić, Kaja Dobrovoljc, Senja Pollak +1
In this paper, we focus on the detection of semantic changes in Slovene, a less resourced Slavic language with two million speakers. Detecting and tracking semantic changes provide…
A bilingual approach to specialised adjectives through word embeddings in the karstology domain
Larisa Grčić Simeunović, Matej Martinc, Špela Vintar
We present an experiment in extracting adjectives which express a specific semantic relation using word embeddings. The results of the experiment are then thoroughly analysed and c…