Does XLM-R follows RoBERTa or XLM for MLM?

Hugging Face states that:

>It is based on Facebook’s RoBERTa model released in 2019. It is a large multi-lingual language model, trained on 2.5TB of filtered CommonCrawl data.

While XLM-R paper states:

>We follow the XLM approach as closely as possible, only introducing changes that improve performance at scale.

The confusion is RoBERTa uses dynamic masking whereas XLM uses static one. Also, RoBERTa uses 512 tokens max for input while XLM uses 256. Also, I didn’t understood the following XLM …

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