Reviewers must have research experience equivalent to a second-year graduate student in machine learning or a related field. They must have been a primary author* on at least two peer-reviewed conference or journal papers published in a related venue (e.g., ACL, NAACL, EMNLP, ICML, NeurIPS, ICLR, JMLR, TMLR, CVPR, ICCV – this is not an exhaustive list). We strongly encourage each first-time reviewer to identify a ‘mentor’ (such as a research advisor or manager) who has both the necessary qualifications for and prior experience with reviewing, and who has agreed to oversee and assist the reviewer in their reviewing tasks. The research experience ensures the reviewer is to be able to competently evaluate a submission's methodology, interpret findings and results, and to evaluate contributions in the context of prior works. Prior authorship ensures that the reviewer understands the peer review process (at least from the side of the authors) and the standards and conventions of composing reviews and corresponding with authors. This text is adapted from ICML. *We leave it to your own discretion to interpret what is meant by 'primary author', as this may vary between sub-areas of machine learning.