Commonsense Question

Commonsense question answering (CQA) focuses on enabling artificial intelligence to answer questions requiring everyday knowledge, a crucial step towards more human-like AI. Current research emphasizes improving the ability of large language models (LLMs), often leveraging techniques like external knowledge bases and direct model parameter editing (e.g., using algorithms like MEMIT), to enhance performance on diverse CQA datasets. This field is significant because overcoming the limitations of LLMs in commonsense reasoning is vital for building more reliable and useful AI systems across various applications.