Attention is an increasingly popular mechanism used in a wide range of neural
architectures. The mechanism itself has been realized in a variety of formats. However …

This tutorial surveys neural approaches to conversational AI that were developed in the last
few years. We group conversational systems into three categories:(1) question answering …

In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …

Understanding narratives requires reading between the lines, which in turn, requires
interpreting the likely causes and effects of events, even when they are not mentioned …

We present RACE, a new dataset for benchmark evaluation of methods in the reading
comprehension task. Collected from the English exams for middle and high school Chinese …

In this paper, we present the gated self-matching networks for reading comprehension style
question answering, which aims to answer questions from a given passage. We first match …

We consider open-domain queston answering (QA) where answers are drawn from either a
corpus, a knowledge base (KB), or a combination of both of these. We focus on a setting in …

Abstract Machine reading comprehension (MRC) is an AI challenge that requires machines
to determine the correct answers to questions based on a given passage. MRC systems …

First derived from human intuition, later adapted to machine translation for automatic token
alignment, attention mechanism, a simple method that can be used for encoding sequence …

Machine reading is a fundamental task for testing the capability of natural language
understanding, which is closely related to human cognition in many aspects. With the rising …