mlsanityData to 7 Oct 2026

Decentralized Quantum Federated Learning for Metaverse: Analysis, Design and Implementation

arXiv 2306.11297 ↗First posted 20 Jun 2023cs.LGcited by 5

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Abstract (arXiv)

With the emerging developments of the Metaverse, a virtual world where people can interact, socialize, play, and conduct their business, it has become critical to ensure that the underlying systems are transparent, secure, and trustworthy. To this end, we develop a decentralized and trustworthy quantum federated learning (QFL) framework. The proposed QFL leverages the power of blockchain to create a secure and transparent system that is robust against cyberattacks and fraud. In addition, the decentralized QFL system addresses the risks associated with a centralized server-based approach. With extensive experiments and analysis, we evaluate classical federated learning (CFL) and QFL in a distributed setting and demonstrate the practicality and benefits of the proposed design. Our theoretical analysis and discussions develop a genuinely decentralized financial system essential for the Metaverse. Furthermore, we present the application of blockchain-based QFL in a hybrid metaverse powered by a metaverse observer and world model. Our implementation details and code are publicly available 1.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 20 of its 43 references that are in the map. First posted on arXiv 20 Jun 2023.

Builds on

20 of 43 references.

References · 20

  1. 2019On the Convergence of FedAvg on Non-IID Datacited by 1,220
  2. 2022data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Languagecited by 718
  3. 2020Variational Quantum Algorithmscited by 687
  4. 2020The power of quantum neural networkscited by 377
  5. 2021Quantum machine learning beyond kernel methodscited by 91
  6. 2020Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognitioncited by 56
  7. 2021Quantum Federated Learning with Quantum Datacited by 53
  8. 2022Slimmable Quantum Federated Learningcited by 23
  9. 2021QuantumFed: A Federated Learning Framework for Collaborative Quantum Trainingcited by 22
  10. 2020Advances in Quantum Deep Learning: An Overviewcited by 21
  11. 2022Federated Learning with Quantum Secure Aggregationcited by 21
  12. 2021Metaverse for Social Good: A University Campus Prototypecited by 17
8 more
  1. 2022Fusing Blockchain and AI with Metaverse: A Surveycited by 17
  2. 2021Robust Blockchained Federated Learning with Model Validation and Proof-of-Stake Inspired Consensuscited by 14
  3. 2022Federated Quantum Natural Gradient Descent for Quantum Federated Learningcited by 14
  4. 2022HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics in Industrial Metaversecited by 14
  5. 20226G-enabled Edge AI for Metaverse: Challenges, Methods, and Future Research Directionscited by 13
  6. 2022Quantum Distributed Deep Learning Architectures: Models, Discussions, and Applicationscited by 12
  7. 2022A Hybrid Quantum-Classical Neural Network Architecture for Binary Classificationcited by 11
  8. 2022Adaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learningcited by 6

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Cited by year

Citing papers per year: 2024: 1; 2025: 4.

5 papers.

  1. 2025Quantum Federated Learning: A Comprehensive Surveycited by 7
  2. 2024Prospects of Privacy Advantage in Quantum Machine Learningcited by 3
  3. 2025Adversarial Robustness in Distributed Quantum Machine Learningcited by 2
  4. 2025New Insights on Unfolding and Fine-tuning Quantum Federated Learningcited by 1
  5. 2025Quantum Federated Learning: Architectural Elements and Future Directionscited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2024MQFL-FHE: Multimodal Quantum Federated Learning Framework with Fully Homomorphic Encryption
  2. 2026Blockchain Infrastructure for Intelligent Cyber--Physical--Social Systems:Post-Quantum Security, Interoperability, and Trustworthy Data Economies in the Era of Embodied AI
  3. 2022On Decentralizing Federated Reinforcement Learning in Multi-Robot Scenarios
  4. 2024Disentangling data distribution for Federated Learning
  5. 2026Learning to Collaborate: An Orchestrated-Decentralized Framework for Peer-to-Peer LLM Federation
  6. 2021Internet of quantum blockchains: security modeling and dynamic resource pricing for stable digital currency
  7. 2024PDFed: Privacy-Preserving and Decentralized Asynchronous Federated Learning for Diffusion Models
  8. 2025From Privacy to Trust in the Agentic Era: A Taxonomy of Challenges in Trustworthy Federated Learning Through the Lens of Trust Report 2.0