# Quantum Natural Language Processing on Near-Term Quantum Computers

@inproceedings{Meichanetzidis2020QuantumNL, title={Quantum Natural Language Processing on Near-Term Quantum Computers}, author={Konstantinos Meichanetzidis and Stefano Gogioso and Giovanni de Felice and Nicolo Chiappori and Alexis Toumi and Bob Coecke}, booktitle={QPL}, year={2020} }

In this work, we describe a full-stack pipeline for natural language processing on near-term quantum computers, aka QNLP. The language modelling framework we employ is that of compositional distributional semantics (DisCoCat), which extends and complements the compositional structure of pregroup grammars. Within this model, the grammatical reduction of a sentence is interpreted as a diagram, encoding a specific interaction of words according to the grammar. It is this interaction which…

## 33 Citations

### Application of Quantum Natural Language Processing for Language Translation

- Computer ScienceIEEE Access
- 2021

This work proposes a protocol based on quantum long short-term memory (Q-LSTM) for Q-NLP to perform various tasks in general but specifically for translating a sentence from English to Persian, and develops compositional vector-based semantics of positive transitive sentences using quantum natural language processing.

### Parametrized Quantum Circuits of Synonymous Sentences in Quantum Natural Language Processing

- Computer ScienceArXiv
- 2021

In this paper we develop a compositional vector-based semantics of positive transitive sentences in quantum natural language processing for a non-English language, i.e. Persian, to compare the…

### A Quantum Natural Language Processing Approach to Pronoun Resolution

- Computer ScienceArXiv
- 2022

This work uses the Lambek Calculus with soft sub-exponential modalities to model and reason about discourse relations such as anaphora and ellipsis, and develops quantum circuit semantics for discourse relations using truncated Fock spaces.

### Quantum computations for disambiguation and question answering

- Computer ScienceQuantum Inf. Process.
- 2022

This paper introduces a new framework that starts from a grammar that can be interpreted by means of tensor contraction, to build word representations as quantum states that serve as input to a quantum algorithm.

### QNLP: Compositional Models of Meaning on a Quantum Computer ∗

- Education
- 2021

Introduction. DISCOCAT (DIStributional COmpositional CATegorical) (Coecke et al., 2010) is a framework for models of natural language meaning that comes with a rigorous treatment of the interplay…

### Grammar-Aware Question-Answering on Quantum Computers

- Computer ScienceArXiv
- 2020

This work performs the first implementation of an NLP task on noisy intermediate-scale quantum (NISQ) hardware and encodes word-meanings in quantum states and explicitly account for grammatical structure, which even in mainstream NLP is not commonplace, by faithfully hard-wiring it as entangling operations.

### A Quantum Natural Language Processing Approach to Musical Intelligence

- Computer ScienceArXiv
- 2021

This chapter presents Quanthoven, the first proof-of-concept ever built, which demonstrates that it is possible to program a quantum computer to learn to classify music that conveys different meanings and illustrates how such a capability might be leveraged to develop a system to compose meaningful pieces of music.

### Natural Language Processing Meets Quantum Physics: A Survey and Categorization

- Computer ScienceEMNLP
- 2021

This survey reviews representative methods at the intersection of NLP and quantum physics in the past ten years, categorizing them according to the use of quantum theory, the linguistic targets that are modeled, and the downstream application.

### lambeq: An Efficient High-Level Python Library for Quantum NLP

- Computer ScienceArXiv
- 2021

Lambeq is presented, the first high-level Python library for Quantum Natural Language Processing (QNLP), with a detailed hierarchy of modules and classes implementing all stages of a pipeline for converting sentences to string diagrams, tensor networks, and quantum circuits ready to be used on a quantum computer.

### Functorial Language Models (Work In Progress)

- Computer Science
- 2021

Functorial language models are introduced: a principled way to compute probability distributions over word sequences given a monoidal functor from grammar to meaning, which yields a method for training categorical compositional distributional (DisCoCat) models on raw text data.

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