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.
T. Eftimov, Ana Gjorgjevikj, M. Martinc et al.· Scientific Data· 1 citation
This paper proposes a structured protocol to automate AI risk mitigation through a taxonomy-driven analysis of open-source LLM evaluation and security tools, and presents a taxonomy-driven framework applicable to open-source and proprietary solutions.
Afreen Alam, Evgenija Popchanovska, Ana Gjorgjevikj et al.· 0 citations
A two-dimensional framework, specifically tailored for analyzing multilingual embedding benchmarks under dataset scarcity, is proposed and applied on the Slavic-language subset of the MTEB benchmark, revealing severe benchmark sparsity.
Ana Gjorgjevikj, B. Seljak, T. Eftimov· 0 citations
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