Research Area: Machine Learning
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.
Keywords:
Natural Language Processing
Text Mining
Commonsense reasoning
Pre-trained models
Commonsense knowledge acquisition
Author(s) Name: Prajjwal Bhargava , Vincent Ng
Journal name:
Conferrence name: Proceedings of the AAAI Conference on Artificial Intelligence
Publisher name: AAAI
DOI: 10.1609/aaai.v36i11.21496
Volume Information: Volume 36
