activity
20242026
collaborators

7 papers

cs.CY2026

Adaptive Data Collection for Latin-American Community-sourced Evaluation of Stereotypes (LACES)

Guido Ivetta, Pietro Palombini, Sofía Martinelli +5

The evaluation of societal biases in NLP models is critically hindered by a geo-cultural gap, This leaves regions such as Latin America severely underserved, making it impossible t…

cs.CL2025

CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation

Emilio Villa-Cueva, Sholpan Bolatzhanova, Diana Turmakhan +32

Translating cultural content poses challenges for machine translation systems due to the differences in conceptualizations between cultures, where language alone may fail to convey…

cs.HC2025

Towards culturally-appropriate conversational AI for health in the majority world: An exploratory study with citizens and professionals in Latin America

Dorian Peters, Fernanda Espinoza, Marco da Re +3

There is justifiable interest in leveraging conversational AI (CAI) for health across the majority world, but to be effective, CAI must respond appropriately within culturally and…

cs.CL2025

ROSA: Addressing text understanding challenges in photographs via ROtated SAmpling

Hernán Maina, Guido Ivetta, Mateo Lione Stuto +3

Visually impaired people could benefit from Visual Question Answering (VQA) systems to interpret text in their surroundings. However, current models often struggle with recognizing…

cs.CL2025

HESEIA: A community-based dataset for evaluating social biases in large language models, co-designed in real school settings in Latin America

Guido Ivetta, Marcos J. Gomez, Sofía Martinelli +5

Most resources for evaluating social biases in Large Language Models are developed without co-design from the communities affected by these biases, and rarely involve participatory…

cs.CV2024

CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark

David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo +73

Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge pres…