Against the background of what has been termed a reproducibility crisis in\nscience, the NLP field is becoming increasingly interested in, and\nconscientious about, the reproducibility of its results. The past few years\nhave seen an impressive range of new initiatives, events and active research in\nthe area. However, the field is far from reaching a consensus about how\nreproducibility should be defined, measured and addressed, with diversity of\nviews currently increasing rather than converging. With this focused\ncontribution, we aim to provide a wide-angle, and as near as possible complete,\nsnapshot of current work on reproducibility in NLP, delineating differences and\nsimilarities, and providing pointers to common denominators.\n