The meeting between Natural Language Processing (NLP) and Quantum Computing has
been very successful in recent years, leading to the development of several approaches of …

How does language inform our downstream thinking? In particular, how do humans make
meaning from language--and how can we leverage a theory of linguistic meaning to build …

Despite the recent success of deep neural networks in natural language processing and
other spheres of artificial intelligence, their interpretability remains a challenge. We analyze …

Adults can incrementally combine information from speech with astonishing speed to
anticipate future words. Concurrently, a growing body of work suggests that vocabulary …

This paper aims to propose a hierarchical, generative account of diatonic harmonic
progressions and suggest a set of phrase-structure grammar rules. It argues that the …

Argument structure-the pattern of underlying relations between a predicate and its
dependents-is at the base of syntactic theory and the theory of the interface with semantics …

This book introduces formal grammar theories that play a role in current linguistic theorizing
(Phrase Structure Grammar, Transformational Grammar/Government & Binding, Generalized …

This chapter describes how vector space models have been used for document retrieval.
These document‐based models represent the meaning, or topic, of a whole document. It …

This article presents an algorithm for translating the Penn Treebank into a corpus of
Combinatory Categorial Grammar (CCG) derivations augmented with local and long-range …

Intelligent robots frequently need to understand requests from naive users through natural
language. Previous approaches either cannot account for language variation, eg, keyword …