3 citations · 3 across the 4 of their papers we have counts for
5 papers
MindEval2: Clinically Grounded Patients and Rubrics for Evaluating Language Models in Mental Health Support
John Mendonça, Daniel Tschernutter, José Pombal +6
With people increasingly turning to AI chatbots for mental health support, the need to evaluate these tools is becoming more pressing. Recent benchmarks attempt to mimic a realisti…
Move by Move: Measuring and Steering How LLMs Conduct Psychotherapy
Afonso Baldo, Hugo Pitorro, Areti Vassilopoulos +5
As the demand for mental health services outpaces clinical workforce capacity, users are increasingly turning to large language models (LLMs) for accessible and private support. Al…
Risk Governance for Generative AI Mental Health Support: A Multi-Turn Safety Architecture
Anabela C. Areias, Catarina Botelho, António Farinhas +7
Large language models (LLMs) are increasingly used for emotional support despite lacking mechanisms to safely govern evolving mental health risk. Existing safety approaches primari…
MindGuard: Guardrail Classifiers for Multi-Turn Mental Health Support
António Farinhas, Nuno M. Guerreiro, José Pombal +6
Large language models are increasingly used for mental health support, yet their conversational coherence alone does not ensure clinical appropriateness. Existing general-purpose s…
MindEval: Benchmarking Language Models on Multi-turn Mental Health Support
José Pombal, Maya D'Eon, Nuno M. Guerreiro +3
Demand for mental health support through AI chatbots is surging, though current systems present several limitations, like sycophancy or overvalidation, and reinforcement of maladap…