Seminar: Deep Learning Sequence Modelling (Natural Language Processing)
Published in github.com, 2018
Cite with: Das, Neha. (2018). Seminar: Deep Learning Sequence Modelling (Natural Language Processing). http://neha191091.github.io/files/seminar_nlp.pdf
Abstract
Recent experiments with deep learning techniques in the field of sequence modelling tasks in Natural Language Processing (NLP) such as machine translation and text summarizing have been quite successful and have produced improved results over classical methods. This work will take a look at the various deep learning architectures and constructs used to model sequences and aid tasks that involve processing and/or producing sequence data, especially in context of NLP. It would additionally explore in detail, an application of sequence-to-sequence NLP - abstractive text summarization - with particular emphasis on methods from Nallapati et al. (2016)