Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Pereira Jayr"'
Autor:
Fernandes, Leandro Carísio, Dobins, Guilherme Zeferino Rodrigues, Lotufo, Roberto, Pereira, Jayr Alencar
This paper introduces PublicHearingBR, a Brazilian Portuguese dataset designed for summarizing long documents. The dataset consists of transcripts of public hearings held by the Brazilian Chamber of Deputies, paired with news articles and structured
Externí odkaz:
http://arxiv.org/abs/2410.07495
Autor:
Fernandes, Leandro Carísio, Guedes, Gustavo Bartz, Laitz, Thiago Soares, Almeida, Thales Sales, Nogueira, Rodrigo, Lotufo, Roberto, Pereira, Jayr
Document summarization is a task to shorten texts into concise and informative summaries. This paper introduces a novel dataset designed for summarizing multiple scientific articles into a section of a survey. Our contributions are: (1) SurveySum, a
Externí odkaz:
http://arxiv.org/abs/2408.16444
Evaluating the quality of text generated by large language models (LLMs) remains a significant challenge. Traditional metrics often fail to align well with human judgments, particularly in tasks requiring creativity and nuance. In this paper, we prop
Externí odkaz:
http://arxiv.org/abs/2407.14467
This paper presents an approach to enhancing Augmentative and Alternative Communication (AAC) systems by integrating Colourful Semantics (CS) with transformer-based language models specifically tailored for Brazilian Portuguese. We introduce an adapt
Externí odkaz:
http://arxiv.org/abs/2405.15896
Autor:
Bueno, Mirelle, de Oliveira, Eduardo Seiti, Nogueira, Rodrigo, Lotufo, Roberto A., Pereira, Jayr Alencar
Despite Portuguese being one of the most spoken languages in the world, there is a lack of high-quality information retrieval datasets in that language. We present Quati, a dataset specifically designed for the Brazilian Portuguese language. It compr
Externí odkaz:
http://arxiv.org/abs/2404.06976
Autor:
Pereira, Jayr, Assumpcao, Andre, Trecenti, Julio, Airosa, Luiz, Lente, Caio, Cléto, Jhonatan, Dobins, Guilherme, Nogueira, Rodrigo, Mitchell, Luis, Lotufo, Roberto
This paper introduces INACIA (Instru\c{c}\~ao Assistida com Intelig\^encia Artificial), a groundbreaking system designed to integrate Large Language Models (LLMs) into the operational framework of Brazilian Federal Court of Accounts (TCU). The system
Externí odkaz:
http://arxiv.org/abs/2401.05273
Autor:
Santos, Arthur dos, Pereira, Jayr, Nogueira, Rodrigo, Masiero, Bruno, Sander-Tavallaey, Shiva, Zea, Elias
The increasing number of scientific publications in acoustics, in general, presents difficulties in conducting traditional literature surveys. This work explores the use of a generative pre-trained transformer (GPT) model to automate a literature sur
Externí odkaz:
http://arxiv.org/abs/2310.06260
Individuals with complex communication needs (CCN) often rely on augmentative and alternative communication (AAC) systems to have conversations and communique their wants. Such systems allow message authoring by arranging pictograms in sequence. Howe
Externí odkaz:
http://arxiv.org/abs/2308.09497
This paper proposes a question-answering system that can answer questions whose supporting evidence is spread over multiple (potentially long) documents. The system, called Visconde, uses a three-step pipeline to perform the task: decompose, retrieve
Externí odkaz:
http://arxiv.org/abs/2212.09656
Autor:
Pereira, Jayr Alencar, Pereira, Jaylton Alencar, Zanchettin, Cleber, do Nascimento Fidalgo, Robson
Publikováno v:
In Expert Systems With Applications 15 April 2024 240