Papers with Latin America

4 papers
Kreyòl-MT: Building MT for Latin American, Caribbean and Colonial African Creole Languages (2024.naacl-long)

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Challenge: Creole languages are used in much of Latin America, Africa and the Caribbean . a large multilingual bitext like ours has potential to build the best yet or first ever MT models for many languages .
Approach: They present the largest cumulative dataset to date for Creole language MT . they provide MT models supporting all 41 Creoles in 172 translation directions .
Outcome: The proposed model outperforms a genre-specific Creole MT model on its own benchmark for 23 of 34 translation directions.
Adaptive Data Collection for Latin-American Community-sourced Evaluation of Stereotypes (LACES) (2026.findings-acl)

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Challenge: a geo-cultural gap in NLP evaluation hinders evaluation of societal biases . authors propose a new method to collect stereotypes from large language models .
Approach: They propose a new method that integrates sourcing and validation of existing data into a single workflow.
Outcome: The proposed method improves LACES by integrating new stereotype entries and validation of existing data.
NLP Progress in Indigenous Latin American Languages (2024.naacl-long)

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Challenge: a new study examines the marginalization of indigenous languages in the face of rapid technological advancements.
Approach: They highlight the cultural richness of indigenous languages and the risk they face of being overlooked in the realm of natural language processing.
Outcome: The authors highlight the cultural richness of indigenous languages and their risk of being overlooked in the realm of natural language processing.
Unequal Scientific Recognition in the Age of LLMs (2025.findings-emnlp)

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Challenge: a new study evaluates the extent to which popular and frontier LLMs recognize scientists . recognition of scientists remains uneven across gender and geography .
Approach: They evaluate the extent to which popular and frontier LLMs recognize scientists . they compare their outputs against OpenAlex and Wikipedia .
Outcome: The proposed models show that they exhibit selective and inconsistent recognition patterns . women researchers and researchers from Africa, Asia, and Latin America are significantly underrecognized .

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