Quantum natural language processing: Challenges and opportunities
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 …
been very successful in recent years, leading to the development of several approaches of …
QNLP in practice: Running compositional models of meaning on a quantum computer
Abstract Quantum Natural Language Processing (QNLP) deals with the design and
implementation of NLP models intended to be run on quantum hardware. In this paper, we …
implementation of NLP models intended to be run on quantum hardware. In this paper, we …
lambeq: An efficient high-level python library for quantum NLP
We present lambeq, the first high-level Python library for Quantum Natural Language
Processing (QNLP). The open-source toolkit offers a detailed hierarchy of modules and …
Processing (QNLP). The open-source toolkit offers a detailed hierarchy of modules and …
A survey of quantum theory inspired approaches to information retrieval
Since 2004, researchers have been using the mathematical framework of quantum theory in
information retrieval (IR). Quantum theory offers a generalized probability and logic …
information retrieval (IR). Quantum theory offers a generalized probability and logic …
Quantum self-attention neural networks for text classification
An emerging direction of quantum computing is to establish meaningful quantum
applications in various fields of artificial intelligence, including natural language processing …
applications in various fields of artificial intelligence, including natural language processing …
When bert meets quantum temporal convolution learning for text classification in heterogeneous computing
The rapid development of quantum computing has demonstrated many unique
characteristics of quantum advantages, such as richer feature representation and more …
characteristics of quantum advantages, such as richer feature representation and more …
A quantum many-body wave function inspired language modeling approach
The recently proposed quantum language model (QLM) aimed at a principled approach to
modeling term dependency by applying the quantum probability theory. The latest …
modeling term dependency by applying the quantum probability theory. The latest …
Semantic Hilbert space for text representation learning
Capturing the meaning of sentences has long been a challenging task. Current models tend
to apply linear combinations of word features to conduct semantic composition for bigger …
to apply linear combinations of word features to conduct semantic composition for bigger …
Natural language processing meets quantum physics: A survey and categorization
Recent research has investigated quantum NLP, designing algorithms that process natural
language in quantum computers, and also quantum-inspired algorithms that improve NLP …
language in quantum computers, and also quantum-inspired algorithms that improve NLP …
Quantum language model with entanglement embedding for question answering
Quantum language models (QLMs) in which words are modeled as a quantum
superposition of sememes have demonstrated a high level of model transparency and good …
superposition of sememes have demonstrated a high level of model transparency and good …