2 citations · 2 across the 10 of their papers we have counts for
10 papers · 1 filter
Synthetic Rewriting as a Quality Multiplier: Evidence from Portuguese Continued Pretraining
Thales Sales Almeida, Rodrigo Nogueira, Hélio Pedrini
Synthetic data generation through document rewriting has emerged as a promising technique for improving language model pretraining, yet most studies focus on English and do not sys…
CAPITU: A Benchmark for Evaluating Instruction-Following in Brazilian Portuguese with Literary Context
Giovana Kerche Bonás, Roseval Malaquias Junior, Marcos Piau +6
We introduce CAPITU, a benchmark for evaluating instruction-following capabilities of Large Language Models (LLMs) in Brazilian Portuguese. Unlike existing benchmarks that focus on…
Sabiá-4 Technical Report
Thiago Laitz, Thales Sales Almeida, Hugo Abonizio +6
This technical report presents Sabiá-4 and Sabiazinho-4, a new generation of Portuguese language models with a focus on Brazilian Portuguese language. The models were developed thr…
Curió-Edu 7B: Examining Data Selection Impacts in LLM Continued Pretraining
Thales Sales Almeida, Rodrigo Nogueira, Hélio Pedrini
Continued pretraining extends a language model's capabilities by further exposing it to additional data, often tailored to a specific linguistic or domain context. This strategy ha…
PoETa v2: Toward More Robust Evaluation of Large Language Models in Portuguese
Thales Sales Almeida, Ramon Pires, Hugo Abonizio +2
Large Language Models (LLMs) exhibit significant variations in performance across linguistic and cultural contexts, underscoring the need for systematic evaluation in diverse langu…
Building High-Quality Datasets for Portuguese LLMs: From Common Crawl Snapshots to Industrial-Grade Corpora
Thales Sales Almeida, Rodrigo Nogueira, Helio Pedrini
The performance of large language models (LLMs) is deeply influenced by the quality and composition of their training data. While much of the existing work has centered on English,…
Comparing Knowledge Injection Methods for LLMs in a Low-Resource Regime
Hugo Abonizio, Thales Almeida, Roberto Lotufo +1
Large language models (LLMs) often require vast amounts of text to effectively acquire new knowledge. While continuing pre-training on large corpora or employing retrieval-augmente…
TiEBe: Tracking Language Model Recall of Notable Worldwide Events Through Time
Thales Sales Almeida, Giovana Kerche Bonás, João Guilherme Alves Santos +2
As the knowledge landscape evolves and large language models (LLMs) become increasingly widespread, there is a growing need to keep these models updated with current events. While…
SurveySum: A Dataset for Summarizing Multiple Scientific Articles into a Survey Section
Leandro Carísio Fernandes, Gustavo Bartz Guedes, Thiago Soares Laitz +4
Document summarization is a task to shorten texts into concise and informative summaries. This paper introduces a novel dataset designed for summarizing multiple scientific article…
Evaluating GPT-4's Vision Capabilities on Brazilian University Admission Exams
Ramon Pires, Thales Sales Almeida, Hugo Abonizio +1
Recent advancements in language models have showcased human-comparable performance in academic entrance exams. However, existing studies often overlook questions that require the i…