Neural Sequence-to-grid Module for Learning Symbolic Rules

13 Jan 2021 Segwang Kim Hyoungwook Nam Joonyoung Kim Kyomin Jung

Logical reasoning tasks over symbols, such as learning arithmetic operations and computer program evaluations, have become challenges to deep learning. In particular, even state-of-the-art neural networks fail to achieve \textit{out-of-distribution} (OOD) generalization of symbolic reasoning tasks, whereas humans can easily extend learned symbolic rules... (read more)

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