The 2nd FutureDial Challenge: Dialog Systems with Retrieval Augmented Generation (FutureDial-RAG)

Developing intelligent dialog systems has been one of the longest running goals in AI. In recent years, significant progress has been made in building dialog systems with the breakthrough of deep learning methods and the large amount of conversational data being made available for system development (Budzianowski et al., 2018; Ou et al., 2022a; Ouyang et al., 2022; Achiam et al., 2023). There are still full of challenges toward building future dialog systems. The first FutureDial challenge focused on building semi-supervised and reinforced task-oriented dialog systems (FutureDial-SereTOD) (Ou et al., 2022a;b), which was successfully held at EMNLP 2022 SereTOD workshop However, problems like hallucination and fabrication (Alkaissi & McFarlane, 2023) still hinder the usage of such systems in real-life applications like customer service systems, which requires pin-point accuracy. Retrieval augmented generation (RAG) (Lewis et al., 2020; Guu et al., 2020) has been introduced to enhance dialog systems with retrieved information from external knowledge bases and has attracted increasing interests.