activity
20222026
most citedSabiá-2: A New Generation of Portuguese Large Language Models

4 citations · 12 across the 26 of their papers we have counts for

collaborators

28 papers

cs.CL2026

PRISM: Transfer and Limits of Activation Interventions in Tool-Calling Language Models

Giovana Kerche Bonás, Thales Sales Almeida, Marcelo da Silva Reis +2

Recent literature shows that unsafe tool calls can often accompany textual refusals in language models. To investigate this hidden vulnerability, we introduce PRISM, a framework fo…

cs.RO2026

RootSLAM: Square Root Bundle Adjustment for Visual-Inertial SLAM

Tomás Santucci, Mateo de Mayo, Daniel Cremers +1

Efficient perception is a prerequisite for the small, low-power devices targeted by robotics, mixed reality, autonomous driving, and drone applications, all of which rely on Simult…

cs.DL2026

Eleven Years of BRACIS: A Meta-Scientific Study of the Brazilian Conference on Intelligent Systems

Thales Sales Almeida, Giovana Kerche Bonás, Thiago Laitz +7

The Brazilian Conference on Intelligent Systems (BRACIS) is the main national venue for Artificial Intelligence research in Brazil, hosted by the Brazilian Computer Society since 2…

cs.CL2026

BLUEX v2: Benchmarking LLMs on Open-Ended Questions from Brazilian University Entrance Exams

João Guilherme Alves Santos, Giovana Kerche Bonás, Thiago Laitz +2

Although Large Language Models (LLMs) excel in many tasks, their assessment in Portuguese has received less attention, particularly for open-ended, discursive tasks that demand dee…

cs.CL2026

moBERTo: A Modern Encoder for Portuguese via Continued Pretraining of ModernBERT

Thiago Laitz, Thales Sales Almeida, João Guilherme Alves Santos +1

Encoder-only transformer models remain essential for production NLP pipelines. We introduce moBERTo, a Portuguese adaptation of ModernBERT obtained through continued pretraining of…

cs.CL2026

LLM-Based Persuasion Enables Guardrail Override in Frontier LLMs

Rodrigo Nogueira, Thales Sales Almeida, Giovana Kerche Bonás +7

Frontier assistant LLMs ship with strong guardrails: asked directly to write a persuasive essay denying the Holocaust, denying vaccine safety, defending flat-earth cosmology, argui…

cs.CL2026

Magis-Bench: Evaluating LLMs on Magistrate-Level Legal Tasks

Ramon Pires, Thales Sales Almeida, Celio Larcher Junior +6

Existing benchmarks for legal AI focus primarily on tasks where LLMs must produce legal arguments or documents, yet the capacity to \emph{judge} such arguments -- weighing competin…

cs.CL2026

Prosa: Rubric-Based Evaluation of LLMs on Real User Chats in Brazilian Portuguese

Roseval Malaquias Junior, Giovana Kerche Bonás, Thales Sales Almeida +6

Rankings produced by holistic LLM-as-a-judge scoring are sensitive to the bias of the chosen judge model. We show that switching to binary rubric scoring with multi-judge filtering…

cs.CL2026

Measuring Opinion Bias and Sycophancy via LLM-based Persuasion

Rodrigo Nogueira, Giovana Kerche Bonás, Thales Sales Almeida +7

Large language models increasingly shape the information people consume: they are embedded in search, consulted for professional advice, deployed as agents, and used as a first sto…

cs.CL2026

MARCA: A Checklist-Based Benchmark for Multilingual Web Search

Thales Sales Almeida, Giovana Kerche Bonás, Ramon Pires +6

Large language models (LLMs) are increasingly used as sources of information, yet their reliability depends on the ability to search the web, select relevant evidence, and synthesi…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2025

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…

cs.CL2025

Ticket-Bench: A Kickoff for Multilingual and Regionalized Agent Evaluation

Thales Sales Almeida, João Guilherme Alves Santos, Thiago Laitz +1

Large language models (LLMs) are increasingly deployed as task-oriented agents, where success depends on their ability to generate accurate function calls under realistic, multilin…

cs.CL2025

BRoverbs -- Measuring how much LLMs understand Portuguese proverbs

Thales Sales Almeida, Giovana Kerche Bonás, João Guilherme Alves Santos

Large Language Models (LLMs) exhibit significant performance variations depending on the linguistic and cultural context in which they are applied. This disparity signals the neces…

cs.CL2025

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,…

cs.CL2025

BLUEX Revisited: Enhancing Benchmark Coverage with Automatic Captioning

João Guilherme Alves Santos, Giovana Kerche Bonás, Thales Sales Almeida

With the growing capabilities of Large Language Models (LLMs), there is an increasing need for robust evaluation methods, especially in multilingual and non-English contexts. We pr…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

The interplay between domain specialization and model size

Roseval Malaquias Junior, Ramon Pires, Thales Sales Almeida +3

Scaling laws for language models have often focused on finding the optimal model size and token count for training from scratch. However, achieving this optimal balance requires si…

cs.CL2024★ 4 cited

Sabiá-3 Technical Report

Hugo Abonizio, Thales Sales Almeida, Thiago Laitz +4

This report presents Sabiá-3, our new flagship language model, and Sabiazinho-3, a more cost-effective sibling. The models were trained on a large brazilian-centric corpus. Evaluat…

cs.CL2024

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…

cs.CL2024

Measuring Cross-lingual Transfer in Bytes

Leandro Rodrigues de Souza, Thales Sales Almeida, Roberto Lotufo +1

Multilingual pretraining has been a successful solution to the challenges posed by the lack of resources for languages. These models can transfer knowledge to target languages with…