activity
20202025
most citedPirá: A Bilingual Portuguese-English Dataset for Question-Answering about the Ocean

20 citations · 52 across the 17 of their papers we have counts for

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Showing cs.CLShow all

11 papers · 1 filter

cs.CL2025

A RAG-Based Institutional Assistant

Gustavo Kuratomi, Paulo Pirozelli, Fabio G. Cozman +1

Although large language models (LLMs) demonstrate strong text generation capabilities, they struggle in scenarios requiring access to structured knowledge bases or specific documen…

cs.CL2024

Infusing Prompts with Syntax and Semantics

Anton Bulle Labate, Fabio Gagliardi Cozman

Despite impressive success, language models often generate outputs with flawed linguistic structure. We analyze the effect of directly infusing various kinds of syntactic and seman…

cs.CL2024

Question Answering with Texts and Tables through Deep Reinforcement Learning

Marcos M. José, Flávio N. Cação, Maria F. Ribeiro +3

This paper proposes a novel architecture to generate multi-hop answers to open domain questions that require information from texts and tables, using the Open Table-and-Text Questi…

cs.CL2024★ 2 cited

Assessing Good, Bad and Ugly Arguments Generated by ChatGPT: a New Dataset, its Methodology and Associated Tasks

Victor Hugo Nascimento Rocha, Igor Cataneo Silveira, Paulo Pirozelli +2

The recent success of Large Language Models (LLMs) has sparked concerns about their potential to spread misinformation. As a result, there is a pressing need for tools to identify…

cs.CL2023

Assessing Logical Reasoning Capabilities of Encoder-Only Transformer Models

Paulo Pirozelli, Marcos M. José, Paulo de Tarso P. Filho +2

Logical reasoning is central to complex human activities, such as thinking, debating, and planning; it is also a central component of many AI systems as well. In this paper, we inv…

cs.CL2023

Benchmarks for Pirá 2.0, a Reading Comprehension Dataset about the Ocean, the Brazilian Coast, and Climate Change

Paulo Pirozelli, Marcos M. José, Igor Silveira +5

Pirá is a reading comprehension dataset focused on the ocean, the Brazilian coast, and climate change, built from a collection of scientific abstracts and reports on these topics.…

cs.CL2022

BLAB Reporter: Automated journalism covering the Blue Amazon

Yan V. Sym, João Gabriel M. Campos, Fabio G. Cozman

This demo paper introduces the BLAB Reporter, a robot-journalist covering the Brazilian Blue Amazon. The Reporter is based on a pipeline architecture for Natural Language Generatio…

cs.CL2022

Comparing Computational Architectures for Automated Journalism

Yan V. Sym, João Gabriel M. Campos, Marcos M. José +1

The majority of NLG systems have been designed following either a template-based or a pipeline-based architecture. Recent neural models for data-to-text generation have been propos…

cs.CL2022★ 20 cited

Pirá: A Bilingual Portuguese-English Dataset for Question-Answering about the Ocean

André F. A. Paschoal, Paulo Pirozelli, Valdinei Freire +8

Current research in natural language processing is highly dependent on carefully produced corpora. Most existing resources focus on English; some resources focus on languages such…

cs.CL2022★ 6 cited

Integrating question answering and text-to-SQL in Portuguese

Marcos Menon José, Marcelo Archanjo José, Denis Deratani Mauá +1

Deep learning transformers have drastically improved systems that automatically answer questions in natural language. However, different questions demand different answering techni…

cs.CL2020★ 3 cited

An Empirical Accuracy Law for Sequential Machine Translation: the Case of Google Translate

Lucas Nunes Sequeira, Bruno Moreschi, Fabio Gagliardi Cozman +1

In this research, we have established, through empirical testing, a law that relates the number of translating hops to translation accuracy in sequential machine translation in Goo…