Datasets:

BSC-LT
/

multi_lmentry

@@ -151,7 +151,7 @@ The motivation is to provide a **systematic, multilingual benchmark** for assess
 ## Acknowledgements
-Roberto Navigli acknowledges the support, while Simone Conia is fully funded by, the PNRR MUR project [PE0000013-FAIR](https://fondazione-fair.it).
 The authors gratefully acknowledge the support of the AI Factory IT4LIA project and the CINECA award FAIR_NLP under the ISCRA initiative for granting access high-performance computing resources.

 ## Acknowledgements
+We gratefully acknowledge the support of Future AI Research ([PNRR MUR project PE0000013-FAIR](https://fondazione-fair.it/en/)).
 The authors gratefully acknowledge the support of the AI Factory IT4LIA project and the CINECA award FAIR_NLP under the ISCRA initiative for granting access high-performance computing resources.