collaborators

5 papers

cs.AI2026

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…

cs.AI2026

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),…

cs.AI2026

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…

cs.CL2024

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…

cs.CL2024

GPT-4 on Clinic Depression Assessment: An LLM-Based Pilot Study

Giuliano Lorenzoni, Pedro Elkind Velmovitsky, Paulo Alencar +1

Depression has impacted millions of people worldwide and has become one of the most prevalent mental disorders. Early mental disorder detection can lead to cost savings for public…