Extreme Multilabel Classification (XMLC) is an active and rapidly growing research area that deals with the problem of labeling an item with a small set of tags out of an extremely large number of potential tags. Applications include content understanding, document tagging, image tagging, biological sequence tagging, recommendation, etc. While the difficulty and the potential applications of XMLC are well understood in the core machine learning community, to the best of our knowledge, XMLC has not made inroads in the field of Information Retrieval (IR) and related areas. The aim of this workshop is to bring researchers from academia and industry in order to further advance this exciting field and come up with potential applications of XMLC in new areas. We envision a gathering of researchers and practitioners either currently working on XMLC, or using XMLC algorithms for their products, or who may use XMLC in the future. There are invited talks from many renowned researchers in this area, in addition to talks for accepted papers. We welcome researchers from a variety of backgrounds: core ML, recommendations, applications of XMLC in video and image tagging, speech processing, IR etc.