Prompting Contrastive Explanations for Commonsense Reasoning Tasks

@article{Paranjape2021PromptingCE,
  title={Prompting Contrastive Explanations for Commonsense Reasoning Tasks},
  author={Bhargavi Paranjape and Julian Michael and Marjan Ghazvininejad and Luke Zettlemoyer and Hanna Hajishirzi},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.06823}
}
Many commonsense reasoning NLP tasks involve choosing between one or more possible answers to a question or prompt based on knowledge that is often implicit. Large pretrained language models (PLMs) can achieve near-human performance on such tasks, while providing little human-interpretable evidence of the underlying reasoning they use. In this work, we show how to use these same models to generate such evidence: inspired by the contrastive nature of human explanations, we use PLMs to complete… Expand

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