In addition, we introduce a similar approach that instead uses the same objective function that was used to learn the original skip-gram embeddings.
we first train a standard skip-gram model, and then learn from the additional contexts in a second training stage as if they form a separate corpus: We call this approach skip-gram retrofitting.