Author(s)

Yun Li, ShuRui Xiao^*

Affiliation(s)

School of Finance and Economics, Hainan Vocational University of Science and Technology, Haikou 571126, Hainan, China.

Corresponding Author

ShuRui Xiao

ABSTRACT

This paper surveys recent research on the integration of blockchain technology and Large Language Models (LLMs), examining how decentralization, immutability, and cryptographic verification can address challenges in AI governance, data sovereignty, and model accountability. We review key integration strategies including blockchain-based data repositories, smart contract-driven governance mechanisms, and decentralized AI marketplaces. Our analysis identifies three primary application domains—cybersecurity, healthcare data sharing, and financial services—where this convergence demonstrates practical value. However, significant barriers remain: current blockchain throughput falls short of high-frequency AI requirements, privacy-preserving techniques introduce substantial computational overhead, and regulatory frameworks have yet to reconcile blockchain immutability with data protection mandates. We conclude by proposing prioritized research directions to bridge these gaps.

KEYWORDS

Blockchain; Large language models; Decentralization; Smart contracts; Federated learning

CITE THIS PAPER

Yun Li, ShuRui Xiao. Blockchain and large language models: a survey of integration approaches and open challenges. World Journal of Information Technology. 2025, 3(5): 16-20. DOI: https://doi.org/10.61784/wjit3062.

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