Language Models Perform Reasoning via Chain of Thought

Posted by Jason Wei and Denny Zhou, Research Scientists, Google Research, Brain team

In recent years, scaling up the size of language models has been shown to be a reliable way to improve performance on a range of natural language processing (NLP) tasks. Today’s language models at the scale of 100B or more parameters achieve strong performance on tasks like sentiment analysis and machine translation, even with little or no training examples. Even the largest language models, however, …

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