Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21) Knowledge-Aware Dialogue Generation via Hierarchical Infobox Accessing and Infobox-Dialogue Interaction Graph Network Sixing Wu1 , Minghui Wang2 , Dawei Zhang1 , Yang Zhou3 , Ying Li4;5∗ and Zhonghai Wu4;5 1School of Electronics Engineering and Computer Science, Peking University, Beijing, China 2School of Software and Microelectronics , Peking University, Beijing, China 3Auburn University, Auburn, Alabama, USA 4National Research Center of Software Engineering, Peking University, Beijing, China 5Key Lab of High Confidence Software Technologies (MOE), Peking University, Beijing, China fwusixing, minghui wang, daweizhang, li.ying,
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[email protected] Abstract Due to limited knowledge carried by queries, tra- ditional dialogue systems often face the dilemma of generating boring responses, leading to poor user experience. To alleviate this issue, this pa- per proposes a novel infobox knowledge-aware dialogue generation approach, HITA-Graph, with three unique features. First, open-domain infobox tables that describe entities with relevant attributes Figure 1: The ‘Bill Gates’ Infobox from Wikipedia. are adopted as the knowledge source. An order- irrelevance Hierarchical Infobox Table Encoder is proposed to represent an infobox table at three lev- dialogue context [Yu et al., 2020]; namely, it can effectively els of granularity. In addition, an Infobox-Dialogue assist the dialogue systems in understanding the intrinsic se- Interaction