3 citations · 8 across the 24 of their papers we have counts for
5 papers · 2 filters
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…
IndicQE-APE: A Consolidated Benchmark for Quality Estimation and Automatic Post-Editing for Indic Languages
Diptesh Kanojia, Archchana Sindhujan, Sourabh Deoghare +14
Indic quality estimation (QE) and automatic post-editing (APE) data is spread across separate releases, so no single resource supports training and evaluation across tasks and lang…
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…
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…
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…