← Search

Enzo Ferrante

4 accepted papers

2026

Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation

ICLR 2026poster

The evaluation of vision-language models (VLMs) has mainly relied on English-language benchmarks, leaving significant gaps in both multilingual and multicultural coverage. While multilingual benchmarks have expanded, both in size and language, many rely on translations of English datasets, failing t…

Cited by 0SourcecodeScholar
2025

Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation

ACL 2025long

Reliable multilingual evaluation is difficult, and culturally appropriate evaluation is even harder to achieve.A common practice to fill this gap is to machine-translate English evaluation sets. However, translation introduces language bias and carries over cultural and regional assumptions from the…

Cited by 0SourcePDFScholar
2024

ViG-Bias: Visually Grounded Bias Discovery and Mitigation

ECCV 2024poster

"The proliferation of machine learning models in critical decision-making processes has underscored the need for bias discovery and mitigation strategies. Identifying the reasons behind a biased system is not straightforward, since in many occasions they are associated with hidden spurious correlati…