The repo is well structured, with every files placed in right place, it’s easy to find every file. The graphs used in the paper are labelled clearly. The use of clear data visualization techniques enhances the comprehensibility of arguments.
[✅] LLM Usage: included in the Readme and with the file of conversations with ChatGPT.
[✅] : Abstract is clearly
[✅] :Introduction done
However, there are few shortcomings better to be fixed to ensure the quality of the project:
[❌] The paper seems like not all finished, completing the missing parts(results, discussion and conclusion) is necessary.
[❌] It’s better to add some explanations for each data visualization.
[❌] “Data Processing” also misses the process how you deal with the data
[❌] Deeper examination of the study’s limitations will provide a more comprehensive understanding of findings.
And there is one more suggestion on the structure of paper. You made a subsection(data visualization ) for graphs, it organized these graphs well. But when readers read the paper, it might be little hard to read together according to the graphs and results. I suggest that each figures can be placed on the corresponding results to help readers understand better.
I believe authors are still working on the paper. Expanding these sections would greatly contribute to the paper’s overall impact and relevance.
Hi Dingning, thank you very much for the feedback. I've taken these points to discuss with my team and will continue to work to complete the remaining sections of the paper.
The repo is well structured, with every files placed in right place, it’s easy to find every file. The graphs used in the paper are labelled clearly. The use of clear data visualization techniques enhances the comprehensibility of arguments.
[✅] LLM Usage: included in the Readme and with the file of conversations with ChatGPT.
[✅] : Abstract is clearly
[✅] :Introduction done
However, there are few shortcomings better to be fixed to ensure the quality of the project:
[❌] The paper seems like not all finished, completing the missing parts(results, discussion and conclusion) is necessary.
[❌] It’s better to add some explanations for each data visualization.
[❌] “Data Processing” also misses the process how you deal with the data
[❌] Deeper examination of the study’s limitations will provide a more comprehensive understanding of findings.
And there is one more suggestion on the structure of paper. You made a subsection(data visualization ) for graphs, it organized these graphs well. But when readers read the paper, it might be little hard to read together according to the graphs and results. I suggest that each figures can be placed on the corresponding results to help readers understand better.
I believe authors are still working on the paper. Expanding these sections would greatly contribute to the paper’s overall impact and relevance.