output
20022026
most citedVLBA determination of the distance to nearby star-forming regions I. The distance to T Tauri with 0.4% accuracy

182 citations

22 papers

cs.CL2026

Scalable Construction of a Lung Cancer Knowledge Base: Profiling Semantic Reasoning in LLMs

Cesar Felipe Martínez Cisneros, Jesús Ulises Quiroz Bautista, Claudia Anahí Guzmán Solano +5

The integration of Large Language Models (LLMs) into biomedical research offers new opportunities for domainspecific reasoning and knowledge representation. However, their performa…

math.NT2022

Wang-Sun Formula in

Octavio A. Agustín-Aquino

Wang and Sun proved a certain summatory formula involving derangements and primitive roots of the unit. We study such a formula but for the particular case of the set of affine der…

cs.CL2021

Common Sense Knowledge Learning for Open Vocabulary Neural Reasoning: A First View into Chronic Disease Literature

Ignacio Arroyo-Fernández, José Armando Sánchez-Rojas, Arturo Tellez-Velázquez +4

In this paper, we address reasoning tasks from open vocabulary Knowledge Bases (openKBs) using state-of-the-art Neural Language Models (NLMs) with applications in scientific litera…

math.HO2021★ 2 cited

Musicological, computational and conceptual aspects of first-species counterpoint theory

Juan Sebastián Arias-Valero, Octavio Alberto Agustín-Aquino, Emilio Lluis-Puebla

We re-create the essential results of a 1989 unpublished article by Mazzola and Muzzulini that contains musicological aspects of a first-species counterpoint model. We include a su…

math.RA2020★ 1 cited

On first-species counterpoint theory

Juan Sebastián Arias-Valero, Octavio A. Agustín-Aquino, Emilio Lluis-Puebla

We generalize first-species counterpoint theory to arbitrary rings and obtain some new counting and maximization results that enrich the theory of admitted successors, pointing to…

cs.LG2019

On the Possibility of Rewarding Structure Learning Agents: Mutual Information on Linguistic Random Sets

Ignacio Arroyo-Fernández, Mauricio Carrasco-Ruíz, J. Anibal Arias-Aguilar

We present a first attempt to elucidate a theoretical and empirical approach to design the reward provided by a natural language environment to some structure learning agent. To th…