Evaluating the Performance of Large Language Models for Spanish Language in Undergraduate Admissions Exams

• Autores: Sabino Miranda, Obdulia Pichardo Lagunas, Bella Martínez-Seis, Pierre Baldi
• Localización: Computación y Sistemas (CyS), ISSN 1405-5546, ISSN-e 2007-9737, Vol. 27, Nº. 4, 2023, págs. 1241-1248
• Idioma: inglés
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  • Abstract: This study evaluates the performance of large language models, specifically GPT-3.5 and BARD (supported by Gemini Pro model), in un-dergraduate admissions exams proposed by the National Polytechnic Institute in Mexico. The exams cover Engineering/Mathematical and Physical Sciences, Biological and Medical Sciences, and Social and Administrative Sciences. Both models demonstrated proficiency, exceeding the minimum acceptance scores for respective academic programs to up to 75% for some academic programs. GPT-3.5 outperformed BARD in Mathematics and Physics, while BARD performed better in History and questions related to factual information. Overall, GPT-3.5 marginally surpassed BARD with scores of 60.94% and 60.42%, respectively.