collaborators

5 papers

cs.CL2026

Estimating Uncertainty from Reasoning: A Large-Scale Study of Multi- and Crosslingual MCQA Performance in LLMs

Andrea Bacciu, Andrea Alfarano, Saab Mansour +2

Uncertainty estimation (UE) enables LLM-powered systems to recognize when to abstain, yet existing research has predominantly focused on English. We present the first large-scale e…

cs.CL2026

Select, Label, Evaluate: Active Testing in NLP

Antonio Purificato, Maria Sofia Bucarelli, Andrea Bacciu +2

Human annotation cost and time remain significant bottlenecks in Natural Language Processing (NLP), with test data annotation being particularly expensive due to the stringent requ…

cs.CL2026

Cross-Lingual LLM-Judge Transfer via Evaluation Decomposition

Ivaxi Sheth, Zeno Jonke, Amin Mantrach +1

As large language models are increasingly deployed across diverse real-world applications, extending automated evaluation beyond English has become a critical challenge. Existing e…

cs.CL2025

Multilingual Self-Taught Faithfulness Evaluators

Carlo Alfano, Aymen Al Marjani, Zeno Jonke +3

The growing use of large language models (LLMs) has increased the need for automatic evaluation systems, particularly to address the challenge of information hallucination. Althoug…

cs.CL2025

Monte Carlo Temperature: a robust sampling strategy for LLM's uncertainty quantification methods

Nicola Cecere, Andrea Bacciu, Ignacio Fernández Tobías +1

Uncertainty quantification (UQ) in Large Language Models (LLMs) is essential for their safe and reliable deployment, particularly in critical applications where incorrect outputs c…