Improving Smart Contract Code with LLMs

Author:

Klimek Radoslaw1

Affiliation:

1. AGH University of Kraków, Poland

Publisher

University of Gdańsk

Reference4 articles.

1. [1] He, Z., Li, Z., Yang, S., Qiao, A., Zhang, X., Luo, X., Chen, T.: Large language models for blockchain security: A systematic literature review. arXiv (2024), https://arxiv.org/abs/2403.14280

2. [2] Ma, W., Wu, D., Sun, Y., Wang, T., Liu, S., Zhang, J., Xue, Y., Liu, Y.: Combining finetuning and llm-based agents for intuitive smart contract auditing with justifications. arXiv (2024), https://arxiv.org/abs/2403.16073

3. [3] Shou, C., Liu, J., Lu, D., Sen, K.: Llm4fuzz: Guided fuzzing of smart contracts with large language models. arXiv (2024). https://doi.org/10.48550/ARXIV.2401.11108,

4. [4] Zhao, J., Chen, X., Yang, G., Shen, Y.: Automatic smart contract comment generation via large language models and in-context learning. Information and Software Technology 168, 107405 (2024).

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