Retrospectives: A Venue for Self-Reflection in ML Research

The NeurIPS Workshop on Retrospectives in Machine Learning will kick-start the exploration of a new kind of scientific publication, called retrospectives. The purpose of a retrospective is to answer the question:

“What should readers of this paper know now, that is not in the original publication?”

Retrospectives provide a venue for authors to reflect on their previous publications, to talk about how their intuitions have changed, to identify shortcomings in their analysis or results, and to discuss resulting extensions that may not be sufficient for a full follow-up paper. A retrospective is written about a single paper, by that paper's author, and takes the form of an informal paper. The overarching goal of retrospectives is to improve the science, openness, and accessibility of the machine learning field, by widening what is publishable and helping to identifying opportunities for improvement. Retrospectives will also give researchers and practitioners who are unable to attend top conferences access to the author’s updated understanding of their work, which would otherwise only be accessible to their immediate circle.