AI-Assisted Systematic Reviews of Medical Literature
We develop multi-agentic systems to support Evidence-Based Medicine.
Research Group
Agentic Complex Systems
We study emergent phenomena and capabilities within and across generative systems trained for natural language communication.
The emergence of minds from societies of mindless components.
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Current Projects
AI Safety and Alignment Auditing
We develop methods to evaluate robustness, harmful prompt detection, and alignment dynamics in large language models.
Collective Intelligence in Multi-Agent Systems
We analyze coordination, cooperation, and emergent behavior in interacting agents at scales beyond individual human oversight.
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Medium
- April 2026. Luiz Felipe Guain Teixeira. Large Language Models for Systematic Reviews: What Multi-Agent Approaches Can Teach Us. Medium
- March 2026. Eduardo Amorim. Robustness of Language Models against Harmful Prompts in an Underrepresented Language. Medium
- March 2026. Felippe Alves. Emergent Misalignment: sneaky general misbehavior from a few specific bad examples. Medium
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Publications
- 2026. E. A. Amorim, C. Zanchettin. Robustness of Language Models against Portuguese Harmful Prompts.
- 2025. D. B. Costa, F. Alves, R. Vicente. Moral Susceptibility and Robustness under Persona Role-Play in Large Language Models. arXiv:2511.08565.
- 2025. D. B. Costa, R. Vicente. Deceive, Detect, and Disclose: Large Language Models Play Mini-Mafia. arXiv:2509.23023.
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Journal Club
Every week, we choose one paper as a pretext for discussion and idea generation.
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Our Team
Coordinators
Postdocs
PhD Students
Master Students
Undergrad Students
Associated Researchers
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Support
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Contact Us
TELUS Digital Research Hub
Center for Artifical Intelligence and Machine Learning (CIAAM-USP)
rvicente@usp.br