Persian Conversational Question Answering

Persian Conversational Question Answering (CQA) research focuses on developing systems that can understand and respond to multi-turn questions in Persian, going beyond simple question-answer pairs. Current efforts concentrate on improving model performance by combining large language models (LLMs) with techniques like contextual keyword extraction to better capture conversational nuances and handle implicit questions. This research is driven by the need for more sophisticated question answering systems in Persian, facilitated by the creation of new, publicly available datasets specifically designed for evaluating and training CQA models in this language. The resulting advancements will have significant implications for various applications, including improved information access and user engagement in Persian-speaking communities.