and incorrect answers; improving factual generations of language models is an open direction for
future work (Rashkin et al., 2021; Ye and Durrett, 2022; Wiegreffe et al., 2022, inter alia). Finally,
the emergence of chain-of-thought reasoning only at large model scales makes it costly to serve in
real-world applications; further research could explore how to induce reasoning in smaller models.
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models