Showing 421–434 of 26,903 results for "Érika Akemi Tsujiguchi Bernardi"

Journals 2025 UN

Tverberg Partition Graphs

Déborah Oliveros · Érika Roldán · Pablo Soberón +1 more
Society for Industrial and Applied Mathematics
Journals 2025 EN

Planar Kolmogorov systems with infinitely many singular points at infinity

Érika Diz-Pita · Jaume Llibre · M. Victoria Otero-Espinar

We classify the global dynamics of the five-parameter family of planarKolmogorov systems \begin{equation*} \begin{split} \dot{y}&=y \left( b_0+ b_1 y z + b_2 y + b_3 z\right), \dot{z}&=z\left( c_0 + b_1 y z + b_2 y + b_3 z\right), \end{split} \end{equation*} which is obtained from the Lotka-Volterra systemsof dimension three. These systems have infinitely many singular points atinifnity. We give the topological classification of their phase portraits inthe Poincar\'e disc, so we can describe the dynamics of these systems nearinfinity. We prove that these systems have 13 topologically distinct globalphase portraits.

World Scientific
Conference Proceedings 2025 EN

A Matter of Perspective(s): Contrasting Human and LLM Argumentation in Subjective Decision-Making on Subtle Sexism

Paula Akemi Aoyagui · Kelsey Stemmler · Sharon Ferguson +2 more

In subjective decision-making, where decisions are based on contextualinterpretation, Large Language Models (LLMs) can be integrated to present userswith additional rationales to consider. The diversity of these rationales ismediated by the ability to consider the perspectives of different socialactors. However, it remains unclear whether and how models differ in thedistribution of perspectives they provide. We compare the perspectives taken byhumans and different LLMs when assessing subtle sexism scenarios. We show thatthese perspectives can be classified within a finite set (perpetrator, victim,decision-maker), consistently present in argumentations produced by humans andLLMs, but in different distributions and combinations, demonstratingdifferences and similarities with human responses, and between models. We arguefor the need to systematically evaluate LLMs' perspective-taking to identifythe most suitable models for a given decision-making task. We discuss theimplications for model evaluation.

Cornell University