Results 31 to 40 of about 2,678,709 (132)

Is there Gender bias and stereotype in Portuguese Word Embeddings? [PDF]

open access: yesThe 13th edition of the International Conference on the Computational Processing of Portuguese (PROPOR 2018), 2018
In this work, we propose an analysis of the presence of gender bias associated with professions in Portuguese word embeddings. The objective of this work is to study gender implications related to stereotyped professions for women and men in the context of the Portuguese language.
arxiv  

Towards Syntactic Iberian Polarity Classification [PDF]

open access: yesarXiv, 2017
Lexicon-based methods using syntactic rules for polarity classification rely on parsers that are dependent on the language and on treebank guidelines. Thus, rules are also dependent and require adaptation, especially in multilingual scenarios. We tackle this challenge in the context of the Iberian Peninsula, releasing the first symbolic syntax-based ...
arxiv  

Enhancing Portuguese Variety Identification with Cross-Domain Approaches [PDF]

open access: yesarXiv
Recent advances in natural language processing have raised expectations for generative models to produce coherent text across diverse language varieties. In the particular case of the Portuguese language, the predominance of Brazilian Portuguese corpora online introduces linguistic biases in these models, limiting their applicability outside of Brazil.
arxiv  

PORTULAN ExtraGLUE Datasets and Models: Kick-starting a Benchmark for the Neural Processing of Portuguese [PDF]

open access: yesarXiv
Leveraging research on the neural modelling of Portuguese, we contribute a collection of datasets for an array of language processing tasks and a corresponding collection of fine-tuned neural language models on these downstream tasks. To align with mainstream benchmarks in the literature, originally developed in English, and to kick start their ...
arxiv  

The First Multilingual Model For The Detection of Suicide Texts [PDF]

open access: yesarXiv
Suicidal ideation is a serious health problem affecting millions of people worldwide. Social networks provide information about these mental health problems through users' emotional expressions. We propose a multilingual model leveraging transformer architectures like mBERT, XML-R, and mT5 to detect suicidal text across posts in six languages - Spanish,
arxiv  

Harnessing deep learning to monitor people's perceptions towards climate change on social media. [PDF]

open access: yesSci Rep
Cardoso AS   +7 more
europepmc   +1 more source

Gap analysis of social science resources for conservation practice. [PDF]

open access: yesConserv Biol
Detoeuf D   +18 more
europepmc   +1 more source

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