Reviewer Best Practices

What makes a good quality review?

Summarize the work, comment on its overall merits and drawbacks, and provide constructive, substantial feedback.

Consider the strength of the technical content. Does the literature review provide sufficient background and motivation for the work? Review the theoretical/experimental depth, strength of analysis, quality of supporting data and results. Is there sufficient benchmarking and validation, are the conclusions supported by the data and analysis, is the flow of information logical? Is there enough information in this paper for the experiments to be reproducible? If not, comment on what additional or supplementary information is needed. Are there any major technical flaws?

Comment on the article’s technical presentation and organization. Consider things like structure of the paper, language, writing style, quality of figures and tables, typos, formatting.

Can I ask authors to cite specific references?

Suggesting specific references, including articles you have authored, if not relevant to the article or at an excessive level, is not permitted.

You are expected to check if the references are current and relevant to the subject. If you feel that the authors have overlooked important prior research, we encourage you to recommend particular topic areas, rather than specific articles, to improve their literature review and/or better highlight the advantages over the state-of-the-art. If there are any irrelevant, inappropriate, or unnecessary references, be sure to mention this in your comments to the authors.

We of course realize that sometimes authors may miss crucial references to seminal work, or even very recent publications that the authors would benefit from seeing, so if you are going to recommend specific references while completing the review, please be sure to explain why you believe they are relevant to the work.

Can I use Artificial Intelligence tools (such as ChatBot, Google Bard, ChatGPT, etc…) to assist me when writing my review?

No. Reviewers conducting peer reviews for IEEE may not share information from an article with public artificial intelligence (AI) platforms for AI generation of text for the reviewer’s report. Doing so is considered a breach of confidentiality because AI systems generally learn from input. All reviewers conducting peer reviews for IEEE are required to provide substantive feedback, writing original review comments for the author’s and editor’s consideration. We expect reviewers to be responsible for comments they return on any article. You were invited to review because of your personal expertise and insight, which cannot be replicated by an AI tool.