Learning sentence embeddings by Natural Language Inference

Unsupervised learning approach seems like a normal way to build word, sentence or document embeddings because it is more generalized such that pre-trained embeddings result can be transfer to other NLP downstream problems. For example, skip-gram in word embeddings and skip-though in sentence embeddings and distributed bag-of-words in paragraph embeddings.

“closeup photo of person carrying professional video recorder” by Laura Lee Moreau on Unsplash