collaborators

5 papers

cs.CL2026

Safety Is Not Universal: The Selective Safety Trap in LLM Alignment

Iago Alves Brito, Walcy Santos Rezende Rios, Julia Soares Dollis +2

Current safety evaluations of large language models (LLMs) create a dangerous illusion of universal protection by aggregating harms under generic categories such as "Identity Hate"…

cs.CL2026

ToxSyn-PT: A Synthetic Fine-Grained Dataset of Minority-Targeted Toxic Language in Portuguese

Iago Alves Brito, Julia Soares Dollis, Fernanda Bufon Farber +2

The development of robust hate speech detection systems remains limited by the lack of large-scale, fine-grained training data, especially for languages beyond English. Existing co…

cs.CL2026

MedPT: A Massive Medical Question Answering Dataset for Brazilian-Portuguese Speakers

Fernanda Bufon Färber, Iago Alves Brito, Julia Soares Dollis +3

While large language models (LLMs) show transformative potential in healthcare, their development remains focused on high-resource languages. This creates a critical barrier for ot…

cs.HC2026

Integrating Personality into Digital Humans: A Review of LLM-Driven Approaches for Virtual Reality

Iago Alves Brito, Julia Soares Dollis, Fernanda Bufon Färber +3

The integration of large language models (LLMs) into virtual reality (VR) environments has opened new pathways for creating more immersive and interactive digital humans. By levera…

cs.HC2026

When Avatars Have Personality: Effects on Engagement and Communication in Immersive Medical Training

Julia S. Dollis, Iago A. Brito, Fernanda B. Färber +5

While virtual reality (VR) excels at simulating physical environments, its effectiveness for training complex interpersonal skills is limited by a lack of psychologically plausible…