A Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics. (arXiv:2103.01403v2 [cs.LG] UPDATED)

Inspired by humans' remarkable ability to master arithmetic and generalize to
unseen problems, we present a new dataset, HINT, to study machines' capability
of learning generalizable concepts at three levels: perception, syntax, and
semantics. Learning agents are tasked to reckon how concepts are perceived from
raw signals such as images (i.e., perception), how multiple concepts are
structurally combined to form a valid expression (i.e., syntax), and how
concepts are realized to afford various reasoning tasks (i.e., semantics), all
in a …

arxiv dataset perception semantics syntax