Figure 2: 
The PERL pivot-based fine-tuning task (Step 2). In this example two tokens are masked, general and good, only the latter is a pivot. The architecture is identical to that of BERT but the MLM task and the masking process are different, taking into account the pivot/non-pivot distinction.

The PERL pivot-based fine-tuning task (Step 2). In this example two tokens are masked, general and good, only the latter is a pivot. The architecture is identical to that of BERT but the MLM task and the masking process are different, taking into account the pivot/non-pivot distinction.

Close Modal
This Feature Is Available To Subscribers Only

or Create an Account

Close Modal
Close Modal
This site uses cookies. By continuing to use our website, you are agreeing to our privacy policy. No content on this site may be used to train artificial intelligence systems without permission in writing from the MIT Press.
Accept