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

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