Quantum Natural Language Processing

Created: Damir Cavar, 2023-06-12

Last change: Damir Cavar, 2023-06-12

The Quantum NLP project in the NLP Lab is currently a reading group focusing on the most recent papers in Quantum NLP. Our goal is to familiarize everybody with the different tools and environments for QNLP.

The reading group meets independently of the NLP Lab weekly meeting at IU-B. If you want to join this meeting, contact Damir Cavar directly.

The papers we are reading are:

• Coecke et al. (2010) Mathematical Foundations for a Compositional Distributional Model of Meaning.
• Coecke (2019) The Mathematics of Text Structure.
• Gogioso (2016) A Corpus-based Toy Model for DisCoCat.
• Bradley et al. (2018) Translating and Evolving: Towards a Model of Language Change in DisCoCat.
• Kartasaklis et al. (2021) lambeq: An Efficient High-Level Python Library for Quantum NLP.
• Widdows et al. (2022) Near-Term Advances in Quantum Natural Language Processing.
• Alexander and Widdows (2023) Quantum Text Encoding for Classification Tasks.
• Lorenz et al. (2021) QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computer.
• Meichanetzidis et al. (2020) Grammar-aware sentence classification on quantum computers.

Tools and Technologies

• tket, a quantum SDK
  • pytket, a quantum computing toolkit and optimizing compiler by Quantinuum
  • pytket-extensions, extension modules for pytket
• Qiskit - Open-Source Quantum Development

Tutorials

• From quantum picturalism to quantum NLP and quantum AI with Bob Coecke
• An introduction to Quantum Natural Language Processing, Nov. 2022 by Amin Karamlou, Marcel Pfaffhauser, and James Wootton
  • related presentation from the QNLP 2022