Commonsense Reasoning in and Over Natural Language

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Knowledge Infused Learning (K-IL): Towards Deep Incorporation of Knowledge in Deep Learning (2019, background): “, Knowledge Graphs) in deep learning, improves information retrieval (Sheth and Kapanipathi 2016), prior research has shown the significance of knowledge in the pursuit of improving NLMs, such as in commonsense reasoning (Liu and Singh 2004).”
Learning Knowledge Graphs for Question Answering through Conversational Dialog (2015, background): “The relational model for reasoning is both flexible and powerful (Liu and Singh, 2004).”
A Systematic Investigation of Commonsense Understanding in Large Language Models (2021, background): “Despite the importance of commonsense understanding in NLP systems (McCarthy et al., 1960; Gunning, 2018; Liu and Singh, 2004), whether commonsense knowledge can be acquired by large language models and through the language modeling objective remains an open question.”
ConceptNet — A Practical Commonsense Reasoning Tool-Kit (2004, background): “On the subject of ConceptNet’s natural language knowledge representation, we have dedicated an entire other paper ( Liu & Singh, 2004a ).”