7 papers
Implicit Bias in LLMs for Transgender Populations
Micaela Hirsch, Marina Elichiry, Blas Radi +6
Large language models (LLMs) have been shown to exhibit biases against LGBTQ+ populations. While safety training may lessen explicit expressions of bias, previous work has shown th…
Adaptive Data Collection for Latin-American Community-sourced Evaluation of Stereotypes (LACES)
Guido Ivetta, Pietro Palombini, SofÃa 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…
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…
Low-resource domain adaptation while minimizing energy and hardware resource consumption
Hernán Maina, Nicolás Wolovick, Luciana Benotti
Training Large Language Models (LLMs) is costly in terms of energy, hardware, and annotated data, often resulting in a positionality rooted in predominant cultures and values (Sant…
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…
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…