44 citations · 52 across the 8 of their papers we have counts for
8 papers
Solving Context Window Overflow in AI Agents
Anton Bulle Labate, Valesca Moura de Sousa, Sandro Rama Fiorini +3
Large Language Models (LLMs) have become increasingly capable of interacting with external tools, granting access to specialized knowledge beyond their training data - critical in…
Episodic Memory in Agentic Frameworks: Suggesting Next Tasks
Sandro Rama Fiorini, Leonardo G. Azevedo, Raphael M. Thiago +3
Agentic frameworks powered by Large Language Models (LLMs) can be useful tools in scientific workflows by enabling human-AI co-creation. A key challenge is recommending the next st…
KIF: A Wikidata-Based Framework for Integrating Heterogeneous Knowledge Sources
Guilherme Lima, João M. B. Rodrigues, Marcelo Machado +6
We present a Wikidata-based framework, called KIF, for virtually integrating heterogeneous knowledge sources. KIF is written in Python and is released as open-source. It leverages…
A Polystore Architecture Using Knowledge Graphs to Support Queries on Heterogeneous Data Stores
Leonardo Guerreiro Azevedo, Renan Francisco Santos Souza, Elton F. de S. Soares +4
Modern applications commonly need to manage dataset types composed of heterogeneous data and schemas, making it difficult to access them in an integrated way. A single data store t…
DevOps and Microservices in Scientific System development
Maximillien de Bayser, Vinicius Segura, Leonardo Guerreiro Azevedo +4
There is a gap in scientific information systems development concerning modern software engineering and scientific computing. Historically, software engineering methodologies have…
Workflow Provenance in the Lifecycle of Scientific Machine Learning
Renan Souza, Leonardo G. Azevedo, Vítor Lourenço +10
Machine Learning (ML) has already fundamentally changed several businesses. More recently, it has also been profoundly impacting the computational science and engineering domains,…
Managing Data Lineage of O&G Machine Learning Models: The Sweet Spot for Shale Use Case
Raphael Thiago, Renan Souza, L. Azevedo +7
Machine Learning (ML) has increased its role, becoming essential in several industries. However, questions around training data lineage, such as "where has the dataset used to trai…
Provenance Data in the Machine Learning Lifecycle in Computational Science and Engineering
Renan Souza, Leonardo Azevedo, Vítor Lourenço +10
Machine Learning (ML) has become essential in several industries. In Computational Science and Engineering (CSE), the complexity of the ML lifecycle comes from the large variety of…