Machine learning systems are becoming increasingly ubiquitous. These systems's adoption
has been expanding, accelerating the shift towards a more algorithmic society, meaning that …

Large language models (LLMs) with hundreds of billions of parameters have sparked a new
wave of exciting AI applications. However, they are computationally expensive at inference …

Text summarization aims at compressing long documents into a shorter form that conveys
the most important parts of the original document. Despite increased interest in the …

Enabling a computer to understand a document so that it can answer comprehension
questions is a central, yet unsolved goal of NLP. A key factor impeding its solution by …

Many recent papers address reading comprehension, where examples consist of (question,
passage, answer) tuples. Presumably, a model must combine information from both …

Artificial intelligence (AI) is a branch of computer science and a technology aimed at
developing the theories, methods, algorithms, and applications for simulating and extending …

How can we enable computers to automatically answer questions like" Who created the
character Harry Potter"? Carefully built knowledge bases provide rich sources of facts …

Recent advances by practitioners in the deep learning community have breathed new life
into Locality Sensitive Hashing (LSH), using it to reduce memory and time bottlenecks in …

We propose a new dataset for evaluating question answering models with respect to their
capacity to reason about beliefs. Our tasks are inspired by theory-of-mind experiments that …

In this chapter, we set up the fundamental framework for the book. We first provide an
introduction to the basics of natural language processing (NLP) as an integral part of …