: Leveraging the broad cross-linguistic data in WALS to improve how models handle the hundreds of languages that lack large amounts of training text.
For more information on the specific data points, you can explore the Official WALS Features List or the WALS-Bench dataset on Hugging Face. WALS roberta sets 37-70.zip
: Gender assignment (32A), coding of nominal plurality (33A), and the number of cases (49A). : Leveraging the broad cross-linguistic data in WALS
The features in this range are essential for understanding how different languages handle noun and verb structures. : The features in this range are essential for
This specific set is often used in for the following purposes:
The "RoBERTa" designation suggests this data has been pre-processed or formatted for use with the (Robustly Optimized BERT Pretraining Approach) large language model, likely for tasks like cross-lingual transfer or testing a model's metalinguistic knowledge. Included Linguistic Features (Chapters 37–70)
: Perfective/imperfective aspect (65A), past tense (66A), future tense (67A), and the perfect (68A).