Web: http://arxiv.org/abs/2103.01403

Sept. 21, 2022, 1:13 a.m. | Qing Li, Siyuan Huang, Yining Hong, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu

cs.CV updates on arXiv.org arxiv.org

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

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