Negative Commonsense

Negative commonsense, encompassing knowledge about what is *not* true regarding everyday concepts, is a crucial yet under-researched area of artificial intelligence. Current research focuses on improving large language models' ability to understand and generate statements reflecting this negative knowledge, often employing techniques like self-supervised learning and knowledge graph construction to overcome biases towards positive information. This work is significant because accurately representing negative commonsense is vital for building more robust and reliable AI systems capable of nuanced reasoning and natural language understanding, impacting applications ranging from question answering to chatbot development.