# Efficient Generation of Parameterised Quantum Circuits from Large Texts

arXiv: https://arxiv.org/abs/2505.13208 · HTML: https://mlsanity.com/paper/2505.13208/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 18 of its 31 references that are in the map.
- First posted on arXiv 19 May 2025.

## Builds on (most cited first, 18 of 18)

- [Supervised learning with quantum enhanced feature spaces](https://mlsanity.com/paper/1804.11326/) (2018)
- [QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computer](https://mlsanity.com/paper/2102.12846/) (2021)
- [lambeq: An Efficient High-Level Python Library for Quantum NLP](https://mlsanity.com/paper/2110.04236/) (2021)
- [The Frobenius anatomy of word meanings I: subject and object relative pronouns](https://mlsanity.com/paper/1404.5278/) (2014)
- [The Mathematics of Text Structure](https://mlsanity.com/paper/1904.03478/) (2019)
- [Open System Categorical Quantum Semantics in Natural Language Processing](https://mlsanity.com/paper/1502.00831/) (2015)
- [Grammar-aware sentence classification on quantum computers](https://mlsanity.com/paper/2012.03756/) (2020)
- [Towards Compositional Interpretability for XAI](https://mlsanity.com/paper/2406.17583/) (2024)
- [Quantum Transformer: Accelerating model inference via quantum linear algebra](https://mlsanity.com/paper/2402.16714/) (2024)
- [Reasoning about Meaning in Natural Language with Compact Closed Categories and Frobenius Algebras](https://mlsanity.com/paper/1401.5980/) (2014)
- [Grammar Equations](https://mlsanity.com/paper/2106.07485/) (2021)
- [Language-independence of DisCoCirc's Text Circuits: English and Urdu](https://mlsanity.com/paper/2208.10281/) (2022)
- [Graded Entailment for Compositional Distributional Semantics](https://mlsanity.com/paper/1601.04908/) (2016)
- [Internal Wiring of Cartesian Verbs and Prepositions](https://mlsanity.com/paper/1811.05770/) (2018)
- [A Pipeline For Discourse Circuits From CCG](https://mlsanity.com/paper/2311.17892/) (2023)
- [Quantum Algorithms for Compositional Text Processing](https://mlsanity.com/paper/2408.06061/) (2024)
- [SimpleBooks: Long-term dependency book dataset with simplified English vocabulary for word-level language modeling](https://mlsanity.com/paper/1911.12391/) (2019)
- [Coordination in Categorical Compositional Distributional Semantics](https://mlsanity.com/paper/1606.01515/) (2016)

## Abstract (arXiv)

Quantum approaches to natural language processing (NLP) are redefining how linguistic information is represented and processed. While traditional hybrid quantum-classical models rely heavily on classical neural networks, recent advancements propose a novel framework, DisCoCirc, capable of directly encoding entire documents as parameterised quantum circuits (PQCs), besides enjoying some additional interpretability and compositionality benefits. Following these ideas, this paper introduces an efficient methodology for converting large-scale texts into quantum circuits using tree-like representations of pregroup diagrams. Exploiting the compositional parallels between language and quantum mechanics, grounded in symmetric monoidal categories, our approach enables faithful and efficient encoding of syntactic and discourse relationships in long and complex texts (up to 6410 words in our experiments) to quantum circuits. The developed system is provided to the community as part of the augmented open-source quantum NLP package lambeq Gen II.