Papers by Viviane Moreira

5 papers
A Large Parallel Corpus of Full-Text Scientific Articles (L18-1)

Copied to clipboard

Challenge: Scielo database contains articles from several research domains.
Approach: They propose to build a parallel corpus from Scielo in three languages: English, Portuguese, and Spanish.
Outcome: The proposed system outperforms other systems on scientific articles in English, Portuguese, and Spanish.
Offensive Video Detection: Dataset and Baseline Results (2020.lrec-1)

Copied to clipboard

Challenge: a large number of social media platforms discourage users from publishing offensive content . however, there is no method to detect offensive content on these platforms due to the high volume of publications.
Approach: They propose to use text-based machine learning to detect offensive content on different platforms . they use word embedding with Deep Learning classifiers to perform best results .
Outcome: The proposed methods outperform Classic and Deep Learning classifiers in Portuguese and CNN architectures in other features.
Embeddings for Named Entity Recognition in Geoscience Portuguese Literature (2020.lrec-1)

Copied to clipboard

Challenge: Named Entity Recognition (NER) is a task within the field of Natural Language Processing that deals with the identification and categorization of Named entities (NEs) in a given text.
Approach: They propose to use vector and tensor embeddings to train Portuguese Named Entity Recognition (NER) in the Geology domain.
Outcome: The proposed model achieves state-of-the-art for the Portuguese Geology domain with one of its embeddings.
Evaluation of Question Answer Generation for Portuguese: Insights and Datasets (2024.findings-emnlp)

Copied to clipboard

Challenge: Automatic question generation is an increasingly important task that can be applied in educational settings, data augmentation for question-answering (QA), and conversational systems.
Approach: They adapt and apply QAG approaches to generate question-answer pairs given context and look into strategies for error filtering and their effects.
Outcome: The proposed methods can generate question-answer pairs in Portuguese, a widely spoken language that is underrepresented in natural language processing research.
InferBR: A Natural Language Inference Dataset in Portuguese (2024.lrec-main)

Copied to clipboard

Challenge: Portuguese has few NLI-annotated datasets created through automatic translation followed by manual checking.
Approach: They propose to generate premises and hypotheses using a semiautomatic process to generate sentences and manually check the annotations.
Outcome: The proposed dataset is better at recognizing entailment classes in other Portuguese datasets than the reverse.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations