Deep learning for reading and understanding language

Thesis

This thesis presents novel tasks and deep learning methods for machine reading comprehension and question answering with the goal of achieving natural language understanding.

First, we consider a semantic parsing task where the model understands sentences and translates them into a logical form or instructions. We present a novel semi-supervised sequential autoencoder that considers language as a discrete sequential latent variable and semantic parses as the observations. This mod...

Expand abstract

Authors: Kočiský, T

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Keywords: Deep Learning; Reading Comprehension; Semantic Parsing
• Subjects: Computer Science; Computational Linguistics; Natural Language Processing