Large Language Models are Zero-Shot Reasoners. (arXiv:2205.11916v1 [cs.CL])

Pretrained large language models (LLMs) are widely used in many sub-fields of
natural language processing (NLP) and generally known as excellent few-shot
learners with task-specific exemplars. Notably, chain of thought (CoT)
prompting, a recent technique for eliciting complex multi-step reasoning
through step-by-step answer examples, achieved the state-of-the-art
performances in arithmetics and symbolic reasoning, difficult system-2 tasks
that do not follow the standard scaling laws for LLMs. While these successes
are often attributed to LLMs' ability for few-shot learning, we show …

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