mlsanityData to 14 Oct 2026

Quantum Long Short-term Memory with Differentiable Architecture Search

arXiv 2508.14955 ↗First posted 20 Aug 2025cs.LG cs.AI cs.ETcited by 4

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Abstract (arXiv)

Recent advances in quantum computing and machine learning have given rise to quantum machine learning (QML), with growing interest in learning from sequential data. Quantum recurrent models like QLSTM are promising for time-series prediction, NLP, and reinforcement learning. However, designing effective variational quantum circuits (VQCs) remains challenging and often task-specific. To address this, we propose DiffQAS-QLSTM, an end-to-end differentiable framework that optimizes both VQC parameters and architecture selection during training. Our results show that DiffQAS-QLSTM consistently outperforms handcrafted baselines, achieving lower loss across diverse test settings. This approach opens the door to scalable and adaptive quantum sequence learning.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 26 of its 34 references that are in the map. First posted on arXiv 20 Aug 2025.

Builds on

26 of 34 references.

References · 26

  1. 2018DARTS: Differentiable Architecture Searchcited by 1,798
  2. 2020Variational Quantum Algorithmscited by 692
  3. 2019Variational Quantum Circuits for Deep Reinforcement Learningcited by 167
  4. 2020Quantum Long Short-Term Memorycited by 120
  5. 2021The Dawn of Quantum Natural Language Processingcited by 61
  6. 2021Quantum Architecture Search via Deep Reinforcement Learningcited by 60
  7. 2022A Survey on Quantum Reinforcement Learningcited by 53
  8. 2024Curriculum reinforcement learning for quantum architecture search under hardware errorscited by 37
  9. 2024Quantum Architecture Search: A Surveycited by 32
  10. 2021Automatic design of quantum feature mapscited by 28
  11. 2022PQLM -- Multilingual Decentralized Portable Quantum Language Model for Privacy Protectioncited by 26
  12. 2022Quantum deep recurrent reinforcement learningcited by 24
14 more
  1. 2024Learning to Program Variational Quantum Circuits with Fast Weightscited by 24
  2. 2023Applying QNLP to sentiment analysis in financecited by 23
  3. 2021Quantum Architecture Search via Continual Reinforcement Learningcited by 22
  4. 2025Learning to Measure Quantum Neural Networkscited by 15
  5. 2022Reservoir Computing via Quantum Recurrent Neural Networkscited by 14
  6. 2023Efficient quantum recurrent reinforcement learning via quantum reservoir computingcited by 14
  7. 2024Differentiable Quantum Architecture Search in Asynchronous Quantum Reinforcement Learningcited by 14
  8. 2023Differentiable Quantum Architecture Search for Quantum Reinforcement Learningcited by 13
  9. 2024Quantum Machine Learning Architecture Search via Deep Reinforcement Learningcited by 13
  10. 2024Reinforcement learning-based architecture search for quantum machine learningcited by 9
  11. 2024Reinforcement Learning for Variational Quantum Circuits Designcited by 9
  12. 2024Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacitycited by 9
  13. 2022AutoQML: Automatic Generation and Training of Robust Quantum-Inspired Classifiers by Using Genetic Algorithms on Grayscale Imagescited by 4
  14. 2024LSTM-QGAN: Scalable NISQ Generative Adversarial Networkcited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 3.

4 papers.

  1. 2025QKAN-LSTM: Quantum-inspired Kolmogorov-Arnold Long Short-term Memorycited by 8
  2. 2026Self-Modulating Quantum Fast-Weight Programmers for Efficient Adaptive Sequential Learningcited by 2
  3. 2026Hybrid Quantum-Classical Neural Architecture Searchcited by 1
  4. 2026Q-DIVER: Integrated Quantum Transfer Learning and Differentiable Quantum Architecture Search with EEG Datacited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Differentiable Quantum Architecture Search in Quantum-Enhanced Neural Network Parameter Generation
  2. 2025Evaluating Parameter-Based Training Performance of Neural Networks and Variational Quantum Circuits
  3. 2024On the relation between trainability and dequantization of variational quantum learning models
  4. 2023Evolutionary-enhanced quantum supervised learning model
  5. 2025Hybrid Quantum-Classical Selective State Space Artificial Intelligence
  6. 2025Q-Fusion: Diffusing Quantum Circuits
  7. 2025DiffQ: Unified Parameter Initialization for Variational Quantum Algorithms via Diffusion Models
  8. 2023Potential and limitations of random Fourier features for dequantizing quantum machine learning