C.4 Numeric and logical reasoning

Numeric and logical reasoning has been a long-studied task in machine learning and natural language
processing (Lev et al., 2004, inter alia). Recent work has also aimed to inject numeric reasoning
abilities in language models in various ways, such as augmenting BERT with a predeﬁned set of
executable operations (Andor et al., 2019), including a graph neural network (Ran et al., 2019), and
using specialized training procedures (Pi˛ekos et al., 2021). Another line of work aims to enable
language models to perform logical or formal reasoning, often by verablizing the rules in natural
language formal rules using language (Clark et al., 2020; Saeed et al., 2021; Liang et al., 2021).

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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models