“…Active Learning with Enriched Queries: Our work also fits into a long line of recent studies on learning with natural enriched queries. As previously mentioned, Angluin's [19] original membership query model can be viewed in this vein, and many types of specific enriched queries such as comparisons [25,4,5,6,3,8,7,26,27,9,28], cluster-queries [29,30,31,32,33,34,35,36,37], mistake queries [38], separation queries [39], and more have been studied since. Our work relies most closely on the general framework for active learning with enriched queries introduced by KLMZ [3] in 2017, which we discuss in greater depth in Section 2.5.…”