The Wikimedia Research team <http://research.wikimedia.org> is developing a new method for automatically recommending sections to add to stub articles. This method uses machine learning to suggest sections that could be added to an article, based on the sections that exist in other articles on similar topics. We think this method could be useful for helping new editors find useful onboarding tasks to do. But before we build anything, we need to test the quality of the recommendations. We are looking for experienced editors to evaluate these recommendations and provide feedback to help us improve them. We have built a testing tool <https://secrec.wmflabs.org> that makes it easy to provide quick, survey-style feedback on the quality of the recommendations, and we are also interested in more detailed feedback on the project feedback talkpage <https://meta.wikimedia.org/wiki/Research_talk:Expanding_Wikipedia_articles_across_languages/Inter_language_approach/Feedback#Feedback_on_specific_articles>. If you are interested in giving us feedback, please get started by reading the instructions <https://meta.wikimedia.org/wiki/Research:Expanding_Wikipedia_articles_across_languages/Inter_language_approach/Feedback#Testing_instructions> here and then start rating articles! If you have questions about the project or more general feedback, you can reach us here <https://meta.wikimedia.org/wiki/Research_talk:Expanding_Wikipedia_articles_across_languages/Inter_language_approach/Feedback#General_feedback_or_questions>. Sincerely, Jonathan Morgan <https://en.wikipedia.org/wiki/User:Jmorgan_(WMF)> & Diego Saez-Trumper <https://en.wikipedia.org/wiki/User:Diego_(WMF)>, Wikimedia Foundation Research