6 papers · 1 filter
Consistent and Distinctive: LLM Benchmark Efficiency via Maximum Independent Set Prompt Selection on Similarity Graphs
Denica Kjorvezir, Marko DjukanoviÄ, Ana Gjorgjevikj +2
Evaluating large language models (LLMs) across comprehensive benchmarks is expensive and time-consuming. We propose a graph-based prompt selection framework that models each benchm…
On the Robustness of Multilingual Text Embedding Rankings Across Learning Tasks, Languages, and Benchmark Datasets
Ana Gjorgjevikj, Barbara KorouÅ¡iÄ 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…
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…
Fusing Semantic, Lexical, and Domain Perspectives for Recipe Similarity Estimation
Denica Kjorvezir, Danilo Najkov, Eva ValenciÄ +4
This research focuses on developing advanced methods for assessing similarity between recipes by combining different sources of information and analytical approaches. We explore th…
Beyond Fine-Tuning: Robust Food Entity Linking under Ontology Drift with FoodOntoRAG
Jan Drole, Ana Gjorgjevikj, Barbara Korouši'c Seljak +1
Standardizing food terms from product labels and menus into ontology concepts is a prerequisite for trustworthy dietary assessment and safety reporting. The dominant approach to Na…
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…