3 papers
cs.CL2026
On the Robustness of Multilingual Text Embedding Rankings Across Learning Tasks, Languages, and Benchmark Datasets
Ana Gjorgjevikj, Barbara Koroušić Seljak, Tome Eftimov
Large-scale multilingual text embedding models play crucial role in both research and industry, yet their behavior in language-specific, multi-task settings remains insufficiently…
cs.CL2026
Evaluation of LLMs in retrieving food and nutritional context for RAG systems
Maks Požarnik Vavken, Matevž Ogrinc, Tome Eftimov +1
In this article, we evaluate four Large Language Models (LLMs) and their effectiveness at retrieving data within a specialized Retrieval-Augmented Generation (RAG) system, using a…
cs.CL2021
FoodChem: A food-chemical relation extraction model
Gjorgjina Cenikj, Barbara Koroušić Seljak, Tome Eftimov
In this paper, we present FoodChem, a new Relation Extraction (RE) model for identifying chemicals present in the composition of food entities, based on textual information provide…