1.** Experimental design * *: This paper describes the experimental design in detail, including the selection of data sets, the setting of experimental environment, the selection of models and the setting of parameters. In this way, readers can clearly understand the process of the experiment, so that it is easier to reproduce the experimental results.
2.** Code disclosure * *: Make the implemented code public and share it on platforms such as GitHub, so that more people can see your implementation, and others can do further research on this basis.
3.** Detailed documentation * *: Provide detailed documentation in the paper, including how to install the dependencies, how to run the code, how to reproduce the results, etc. This will make it easier for readers to understand your work.
4.** Use existing evaluation tools * *: If a model or algorithm is used, it is best to use existing evaluation tools to verify its performance. This will increase the credibility of your work.