Question Answering System

Question answering (QA) systems aim to provide accurate and relevant answers to natural language questions, leveraging advancements in natural language processing (NLP). Current research emphasizes improving accuracy and robustness, particularly by combining large language models (LLMs) with knowledge graphs (KGs) to mitigate issues like hallucinations and improve retrieval of relevant information using techniques like Retrieval Augmented Generation (RAG). This field is significant for enhancing information access across diverse domains, from scholarly research and customer service to specialized areas like biomedicine, and for developing more human-like interactions with digital systems.