# Quantum-Enhanced Natural Language Generation: A Multi-Model Framework with Hybrid Quantum-Classical Architectures

arXiv: https://arxiv.org/abs/2508.21332 · HTML: https://mlsanity.com/paper/2508.21332/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 18 references that are in the map.
- First posted on arXiv 29 Aug 2025.

## Builds on (most cited first, 11 of 11)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RWKV: Reinventing RNNs for the Transformer Era](https://mlsanity.com/paper/2305.13048/) (2023)
- [Variational Quantum Algorithms](https://mlsanity.com/paper/2012.09265/) (2020)
- [The Dawn of Quantum Natural Language Processing](https://mlsanity.com/paper/2110.06510/) (2021)
- [QKSAN: A Quantum Kernel Self-Attention Network](https://mlsanity.com/paper/2308.13422/) (2023)
- [Quantum Adaptive Self-Attention for Quantum Transformer Models](https://mlsanity.com/paper/2504.05336/) (2025)
- [QEEGNet: Quantum Machine Learning for Enhanced Electroencephalography Encoding](https://mlsanity.com/paper/2407.19214/) (2024)
- [Mind's Eye: Image Recognition by EEG via Multimodal Similarity-Keeping Contrastive Learning](https://mlsanity.com/paper/2406.16910/) (2024)
- [NECOMIMI: Neural-Cognitive Multimodal EEG-informed Image Generation with Diffusion Models](https://mlsanity.com/paper/2410.00712/) (2024)
- [Quantum-Enhanced Attention Mechanism in NLP: A Hybrid Classical-Quantum Approach](https://mlsanity.com/paper/2501.15630/) (2025)

## Built on by (most cited first, 4 of 4)

- [Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learning](https://mlsanity.com/paper/2605.06734/) (2026)
- [Quantum Reinforcement Learning-Guided Diffusion Model for Image Synthesis via Hybrid Quantum-Classical Generative Model Architectures](https://mlsanity.com/paper/2509.14163/) (2025)
- [Quantum Adaptive Self-Attention for Financial Rebalancing: An Empirical Study on Automated Market Makers in Decentralized Finance](https://mlsanity.com/paper/2509.16955/) (2025)
- [Quantum-enhanced Large Language Models on Quantum Hardware via Cayley Unitary Adapters](https://mlsanity.com/paper/2605.05914/) (2026)

## Abstract (arXiv)

This paper presents a comprehensive evaluation of quantum text generation models against traditional Transformer/MLP architectures, addressing the growing interest in quantum computing applications for natural language processing. We conduct systematic experiments comparing five distinct models: Transformer (baseline), Quantum Kernel Self-Attention Network (QKSAN), Quantum RWKV (QRWKV), and Quantum Attention Sequence Architecture (QASA) across five diverse datasets including simple sentences, short stories, quantum phrases, haiku poetry, and proverbs. Our evaluation employs multiple metrics including perplexity, BLEU scores, vocabulary diversity, repetition rates, and fluency measures to assess different aspects of text generation quality. The experimental results reveal that while traditional Transformer models maintain overall superiority with the lowest average perplexity (1.21) and highest BLEU-1 score (0.2895), quantum-inspired models demonstrate competitive performance in specific scenarios. Notably, QKSAN achieves a competitive BLEU-1 score of 0.2800 while maintaining zero repetition rates, and QRWKV demonstrates perfect vocabulary diversity (Distinct-1 = 1.000) in certain tasks.