Machine Comprehension with Modified Bi Directional Attention Flow Network
The advancement of of Machine Comprehension (MC) in recent years can be largely attributed to the attention mechanism. We proposed a filtering layer in the multi layer hierarchical neural network architecture that can potentially enhance the performance of the attention mechanism. Our preliminary experimentation on the Stanford Question Answering Dataset (SQuAD) showed that the filtering layer can effectively assist the attention flow layer in Bi Directional Attention Flow (BiDAF) model.