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  • Descripción:

Common Sense Explanations (CoS-E) permite que los modelos de lenguaje de entrenamiento generen automáticamente explicaciones que se pueden usar durante el entrenamiento y la inferencia en un marco novedoso de Commonsense Auto-Generated Explanation (CAGE).

Separar Ejemplos de
'train' 9,741
'validation' 1,221
  • características:
FeaturesDict({
    'abstractive_explanation': Text(shape=(), dtype=tf.string),
    'answer': Text(shape=(), dtype=tf.string),
    'choices': Sequence(Text(shape=(), dtype=tf.string)),
    'extractive_explanation': Text(shape=(), dtype=tf.string),
    'id': Text(shape=(), dtype=tf.string),
    'question': Text(shape=(), dtype=tf.string),
})
  • Cita:
@inproceedings{rajani2019explain,
     title = "Explain Yourself! Leveraging Language models for Commonsense Reasoning",
    author = "Rajani, Nazneen Fatema  and
      McCann, Bryan  and
      Xiong, Caiming  and
      Socher, Richard",
      year="2019",
    booktitle = "Proceedings of the 2019 Conference of the Association for Computational Linguistics (ACL2019)",
    url ="https://arxiv.org/abs/1906.02361"
}