Brazil

BRACIS 2021

Are Foundation Models the Future of AI?

**BRACIS** originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – **SBIA** (22 editions), and the Brazilian Symposium on Neural Networks – **SBRN** (13 editions). **ENIAC** is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. **STIL** is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: **CE-IA**, **CE-IC** and **CE-PLN**.

To access the 10th Brazilian Conference on Intelligent Systems (**BRACIS**), you need to register for the conference.  Please visit the Conference official site to register

[Register now](http://c4ai.inova.usp.br/bracis2021/)

Register now

BRACIS originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – SBIA (22 editions), and the Brazilian Symposium on Neural Networks – SBRN (13 editions). 
ENIAC is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. 
STIL is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: CE-IA, CE-IC and CE-PLN

keynote

Neural machine translation (NMT) nowadays requires an increasing
amount of data and computational power, so succeeding in this task with limited
data and using a single GPU might be challenging. Strategies such as the use
of pre-trained word embeddings, subword embeddings, and data augmentation
solutions can potentially address some issues faced in low-resource experimental settings, but their impact on the quality of translations is unclear. This work
evaluates some of these strategies on two low-resource experiments beyond just
reporting BLEU: errors are categorized on the Portuguese-English pair with the
help of a translator, considering semantic and syntactic aspects. The BPE subword approach has shown to be the most effective solution, allowing a BLEU
increase of 59% p.p. compared to the standard Transformer.

Tackling neural machine translation in low-resource settings: a Portuguese case study

The advance on Question Answering systems has achieved significant results, and new related problems have arisen. Few studies have addressed the Complex Knowledge Base Question Answering (C-KBQA) problem. This work presents an overview of C-KBQA systems. A collection of 54 papers were systematically selected, and a map of the methods, approaches, trends, future directions, and gaps in the C-KBQA research was performed. This study shows that C-KBQA systems need to handle multi-hop and constraint questions, and two approaches are usually used to address this problem.

Uma revisão breve sobre perguntas complexas em bases de conhecimento para sistemas de perguntas e respostas

Premium content

Are Foundation Models the Future of AI?

Downloads

Next from BRACIS 2021

Tackling neural machine translation in low-resource settings: a Portuguese case study

Similar lecture

Ethics of AI: Do the face detection models act with prejudice?

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES