Year: 2025
Type: article
Abstract: We report here a series of detailed statistical analyses on a novel largescale multi-domain Romanian corpus that we use to train a small-language model. We identify the core vocabularies pertaining to six different domain-specific subcorpora and show that they follow the so-called Zipf’s law independent on how we count words. Moreover, we introduce two novel frequency-word maps for a domain-specific subcorpus, one showcasing word ranks and one measuring the deviation of the word structure from a perfect vowel-consonant or consonant-vowel repeating pattern. Finally, we show a few examples of prompt/response instances.
Source: Romanian Journal of Physics
Authors: T.A. DIAC, A.F. NEAGOE, M.C. RAPORTARU, A. OPREA, T2, Ceaus Firica, 145100, Rosiori de Vede, Teleorman, Romania, R.-M. DRAGAN, A. NICOLIN-ZACZEK
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4413878433