LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning

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Abstract:

While designing inductive bias in neural architectures has been widely studied, we hypothesize that transformer networks are flexible enough to learn inductive bias from suitable generic tasks. Here, we replace architecture engineering by encoding inductive bias in the form of datasets. Inspired by Peirce's view that deduction, inductio...More

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