On the explainability of natural language processing deep models
Despite their success, deep networks are used as black-box models with outputs that are not
easily explainable during the learning and the prediction phases. This lack of interpretability …
easily explainable during the learning and the prediction phases. This lack of interpretability …
A comprehensive survey on word representation models: From classical to state-of-the-art word representation language models
Word representation has always been an important research area in the history of natural
language processing (NLP). Understanding such complex text data is imperative, given that …
language processing (NLP). Understanding such complex text data is imperative, given that …
BioWordVec, improving biomedical word embeddings with subword information and MeSH
Distributed word representations have become an essential foundation for biomedical
natural language processing (BioNLP), text mining and information retrieval. Word …
natural language processing (BioNLP), text mining and information retrieval. Word …