Is applying pre-trained model on a different type of corpus called transfer learning?
The basic concept of transfer learning is: Storing knowledge gained from solving one problem and applying it to different but related problem
I guess to be precise this is called Transductive Transfer Learning. In this we learn from the already observed training dataset and then predict the labels of the testing dataset. Even though we do not know the labels of the testing datasets, we can make use of the patterns and additional information present in this data during the learning process.
Refer: Ruder