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Maarten Bosma

2 accepted papers

2022

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

NeurIPS 2022accept

We explore how generating a chain of thought---a series of intermediate reasoning steps---significantly improves the ability of large language models to perform complex reasoning. In particular, we show how such reasoning abilities emerge naturally in sufficiently large language models via a simple…

Cited by 13586SourcePDFScholar
2022

Finetuned Language Models are Zero-Shot Learners

ICLR 2022oral

This paper explores a simple method for improving the zero-shot learning abilities of language models. We show that instruction tuning—finetuning language models on a collection of datasets described via instructions—substantially improves zero-shot performance on unseen tasks. We take a 137B parame…