3 citations · 5 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
Selectively Answering Visual Questions
Julian Martin Eisenschlos, Hernán Maina, Guido Ivetta +1
Recently, large multi-modal models (LMMs) have emerged with the capacity to perform vision tasks such as captioning and visual question answering (VQA) with unprecedented accuracy.…
A methodology to characterize bias and harmful stereotypes in natural language processing in Latin America
Laura Alonso Alemany, Luciana Benotti, Hernán Maina +10
Automated decision-making systems, especially those based on natural language processing, are pervasive in our lives. They are not only behind the internet search engines we use da…
A recipe for annotating grounded clarifications
Luciana Benotti, Patrick Blackburn
In order to interpret the communicative intents of an utterance, it needs to be grounded in something that is outside of language; that is, grounded in world modalities. In this pa…