mlsanityData to 14 Oct 2026

Applying QNLP to sentiment analysis in finance

arXiv 2307.11788 ↗First posted 20 Jul 2023cs.CL cs.AI quant-phcited by 23

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Abstract (arXiv)

As an application domain where the slightest qualitative improvements can yield immense value, finance is a promising candidate for early quantum advantage. Focusing on the rapidly advancing field of Quantum Natural Language Processing (QNLP), we explore the practical applicability of the two central approaches DisCoCat and Quantum-Enhanced Long Short-Term Memory (QLSTM) to the problem of sentiment analysis in finance. Utilizing a novel ChatGPT-based data generation approach, we conduct a case study with more than 1000 realistic sentences and find that QLSTMs can be trained substantially faster than DisCoCat while also achieving close to classical results for their available software implementations.

Key facts. Cited by 23 papers in the map (data through 14 Oct 2026). Builds on 13 of its 33 references that are in the map. First posted on arXiv 20 Jul 2023.

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13 of 33 references.

References · 13

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018Supervised learning with quantum enhanced feature spacescited by 665
  3. 2021Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LMcited by 632
  4. 2021Generalization in quantum machine learning from few training datacited by 216
  5. 2020Quantum Long Short-Term Memorycited by 120
  6. 2020Layerwise learning for quantum neural networkscited by 88
  7. 2021QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computercited by 67
  8. 2021The Dawn of Quantum Natural Language Processingcited by 61
  9. 2021lambeq: An Efficient High-Level Python Library for Quantum NLPcited by 44
  10. 2018Why Self-Attention? A Targeted Evaluation of Neural Machine Translation Architecturescited by 30
  11. 2016Quantum Algorithms for Compositional Natural Language Processingcited by 24
  12. 2021A CCG-Based Version of the DisCoCat Frameworkcited by 16
1 more
  1. 2022A multiclass Q-NLP sentiment analysis experiment using DisCoCatcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 8; 2025: 11; 2026: 4.

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  1. 2024Learning to Program Variational Quantum Circuits with Fast Weightscited by 24
  2. 2025Learning to Measure Quantum Neural Networkscited by 15
  3. 2024Differentiable Quantum Architecture Search in Asynchronous Quantum Reinforcement Learningcited by 14
  4. 2024Quantum-Train-Based Distributed Multi-Agent Reinforcement Learningcited by 14
  5. 2025Toward Large-Scale Distributed Quantum Long Short-Term Memory with Modular Quantum Computerscited by 14
  6. 2024Quantum Machine Learning Architecture Search via Deep Reinforcement Learningcited by 13
  7. 2024Consensus-based Distributed Quantum Kernel Learning for Speech Recognitioncited by 10
  8. 2024Quantum Gradient Class Activation Map for Model Interpretabilitycited by 9
  9. 2024Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacitycited by 9
  10. 2024An Introduction to Quantum Reinforcement Learning (QRL)cited by 7
  11. 2025Adaptive Non-local Observable on Quantum Neural Networkscited by 7
  12. 2025Differentiable Quantum Architecture Search in Quantum-Enhanced Neural Network Parameter Generationcited by 7
11 more
  1. 2025Learning to Program Quantum Measurements for Machine Learningcited by 7
  2. 2025Quantum Long Short-term Memory with Differentiable Architecture Searchcited by 4
  3. 2025Transfer Learning Analysis of Variational Quantum Circuitscited by 3
  4. 2025Introduction to Quantum Machine Learning and Quantum Architecture Searchcited by 3
  5. 2025Breaking Through Barren Plateaus: Reinforcement Learning Initializations for Deep Variational Quantum Circuitscited by 2
  6. 2026Recursive QLSTM with Dynamic Variational Quantum Circuit Adaptationcited by 2
  7. 2026Self-Modulating Quantum Fast-Weight Programmers for Efficient Adaptive Sequential Learningcited by 2
  8. 2025Neural Architecture Search for Quantum Autoencoderscited by 1
  9. 2025Quantum Graph Transformer for NLP Sentiment Classificationcited by 0
  10. 2026MADQRL: Distributed Quantum Reinforcement Learning Framework for Multi-Agent Environmentscited by 0
  11. 2026An Exploratory Evaluation of LLM-Assisted Rewriting of Moderate-Complexity Financial Sentences for DisCoCat-Based Sentiment Analysiscited by 0