activity
20242026
collaborators

5 papers

cs.CL2026

Span-Level Machine Translation Meta-Evaluation

Stefano Perrella, Eric Morales Agostinho, Hugo Zaragoza

Machine Translation (MT) and automatic MT evaluation have improved dramatically in recent years, enabling numerous novel applications. Automatic evaluation techniques have evolved…

cs.CL2025

Estimating Machine Translation Difficulty

Lorenzo Proietti, Stefano Perrella, Vilém Zouhar +2

Machine translation quality has steadily improved over the years, achieving near-perfect translations in recent benchmarks. These high-quality outputs make it difficult to distingu…

cs.CL2025

Preliminary Ranking of WMT25 General Machine Translation Systems

Tom Kocmi, Eleftherios Avramidis, Rachel Bawden +25

We present the preliminary rankings of machine translation (MT) systems submitted to the WMT25 General Machine Translation Shared Task, as determined by automatic evaluation metric…

cs.CL2025

Has Machine Translation Evaluation Achieved Human Parity? The Human Reference and the Limits of Progress

Lorenzo Proietti, Stefano Perrella, Roberto Navigli

In Machine Translation (MT) evaluation, metric performance is assessed based on agreement with human judgments. In recent years, automatic metrics have demonstrated increasingly hi…

cs.CL2024

Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics

Stefano Perrella, Lorenzo Proietti, Pere-Lluís Huguet Cabot +2

Machine Translation (MT) evaluation metrics assess translation quality automatically. Recently, researchers have employed MT metrics for various new use cases, such as data filteri…