collaborators

15 papers

cs.CL2026

Move by Move: Measuring and Steering How LLMs Conduct Psychotherapy

Afonso Baldo, Hugo Pitorro, Areti Vassilopoulos +5

Users increasingly turn to large language models for emotional support, yet little is known about how these models actually conduct a psychotherapy interaction. We introduce an ont…

cs.AI2026

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…

cs.CL2026

EuroBERT: Scaling Multilingual Encoders for European Languages

Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Duarte M. Alves +16

General-purpose multilingual vector representations, used in retrieval, regression and classification, are traditionally obtained from bidirectional encoder models. Despite their w…

cs.CV2026

Can Vision Language Models Judge Action Quality? An Empirical Evaluation

Miguel Monte e Freitas, Rui Henriques, Ricardo Rei +1

Action Quality Assessment (AQA) has broad applications in physical therapy, sports coaching, and competitive judging. Although Vision Language Models (VLMs) hold considerable promi…

cs.CL2026

Self-Preference Bias in Rubric-Based Evaluation of Large Language Models

José Pombal, Ricardo Rei, André F. T. Martins

LLM-as-a-judge has become the de facto approach for evaluating LLM outputs. However, judges are known to exhibit self-preference bias (SPB): they tend to favor outputs produced by…

cs.CL2026

EuroLLM-22B: Technical Report

Miguel Moura Ramos, Duarte M. Alves, Hippolyte Gisserot-Boukhlef +15

This report presents EuroLLM-22B, a large language model trained from scratch to support the needs of European citizens by covering all 24 official European Union languages and 11…