Commonsense Knowledge Reasoning and Generation with Pre-trained Language Models: A Survey

Prajjwal Bhargava and Vincent Ng.
Proceedings of the 36th AAAI Conference on Artificial Intelligence, pp. 12317-12325, 2022.

Click here for the PDF version.

Abstract

While commonsense knowledge acquisition and reasoning has traditionally been a core research topic in the knowledge representation and reasoning community, recent years have seen a surge of interest in the natural language processing community in developing pre-trained models and testing their ability to address a variety of newly designed commonsense knowledge reasoning and generation tasks. This paper presents a survey of these tasks, discusses the strengths and weaknesses of state-of-the-art pre-trained models for commonsense reasoning and generation as revealed by these tasks, and reflects on future research directions.

BibTeX entry

@InProceedings{Bhargava+Ng:22a,
  author = {Prajjwal Bhargava and Vincent Ng},
  title = {Commonsense Knowledge Reasoning and Generation with Pre-trained Language Models: A Survey},
  booktitle = {Proceedings of the 36th AAAI Conference on Artificial Intelligence},
  pages = {12317--12325}, 
  year = 2022}