8 papers
An Agentic LLM-Based Framework for Population-Scale Mental Health Screening
Giuliano Lorenzoni, Paulo Alencar, Donald Cowan
Mental health disorders affect millions worldwide, and healthcare systems are increasingly overwhelmed by the volume of clinical data generated from electronic records, telemedicin…
LLM-X: A Scalable Negotiation-Oriented Exchange for Communication Among Personal LLM Agents
Giuliano Lorenzoni, Paulo Alencar, Donald Cowan
We propose a personal-LLM exchange (LLM-X), a scalable negotiation-oriented environment that enables direct, structured communication across populations of personal agents (LLMs),…
CPEMH: An Agentic Framework for Prompt-Driven Behavior Evaluation and Assurance in Foundation-Model Systems for Mental Health Screening
Giuliano Lorenzoni, Ivens Portugal, Paulo Alencar +1
This paper presents CPEMH, an agentic framework designed to evaluate prompt-driven behavior in foundation-model systems operating on transcript-based datasets for mental-health scr…
Enhancing Software Development with Context-Aware Conversational Agents: A User Study on Developer Interactions with Chatbots
Glaucia Melo, Paulo Alencar, Donald Cowan
Software development is a cognitively intensive process requiring multitasking, adherence to evolving workflows, and continuous learning. With the rise of large language model (LLM…
Variability-Aware Machine Learning Model Selection: Feature Modeling, Instantiation, and Experimental Case Study
Cristina Tavares, Nathalia Nascimento, Paulo Alencar +1
The emergence of machine learning (ML) has led to a transformative shift in software techniques and guidelines for building software applications that support data analysis process…
Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT
Giuliano Lorenzoni, Ivens Portugal, Paulo Alencar +1
This study evaluates fine-tuning strategies for text classification using the DistilBERT model, specifically the distilbert-base-uncased-finetuned-sst-2-english variant. Through st…