Commonsense Question Answering

Commonsense question answering (CQA) focuses on enabling computers to answer questions requiring everyday knowledge and reasoning abilities, going beyond factual recall. Current research emphasizes integrating large language models (LLMs) with external knowledge sources like knowledge graphs, often using graph neural networks or prompt engineering techniques to improve reasoning and interpretability. These advancements aim to enhance the performance and explainability of CQA systems, with implications for building more robust and human-like AI assistants and improving the understanding of how LLMs process and reason with information.