N ews D ialogues: Towards Proactive News Grounded Conversation (2023)

Abstract: Hot news is one of the most popular topics in daily conversations. However, news grounded conversation has long been stymied by the lack of well-designed task definition and scarce data. In this paper, we propose a novel task, Proactive News Grounded Conversation, in which a dialogue system can proactively lead the conversation based on some key topics of the news. In addition, both information-seeking and chit-chat scenarios are included realistically, where the user may ask a series of questions about the news details or express their opinions and be eager to chat. To further develop this novel task, we collect a human-to-human Chinese dialogue dataset NewsDialogues, which includes 1K conversations with a total of 14.6K utterances and detailed annotations for target topics and knowledge spans. Furthermore, we propose a method named Predict-Generate-Rank, consisting of a generator for grounded knowledge prediction and response generation, and a ranker for the ranking of multiple responses to alleviate the exposure bias. We conduct comprehensive experiments to demonstrate the effectiveness of the proposed method and further present several key findings and challenges to prompt future research.

## introduction news, especially hot news, is widely discussed in daily conversations, enabling people to connect to others and engage with the public issues they encounter in everyday life @xcite . however, due to the lack of well-designed task definition and the scarcity of training data, news grounded conversation has almost been neglected in dialogue system research @xcite @xcite . ## proactive news grounded conversation we propose a novel task named proactive news grounded conversation. as shown in figure 1 , a user converses with an agent based on a given news article in each conversation. the conversation begins with the agent, and during the conversation: both chit-chat and information-seeking scenarios are contained naturally. ## newsdialogues to further develop this task, we collect a humanto-human chinese dialogue dataset newsdia-logues. ## conclusion in this paper, we define a novel task named proactive news grounded conversation, where the dialogue system can proactively lead the conversation based on some topics of the news. in addition, we collect newsdialogues with 1k dialogues and rich annotations. furthermore, we propose predict-generate-rank, which consists of a generator trained with a multi-task objective and a ranker trained with contrastive loss. comprehensive experiments have been conducted to investigate the performance of current models on newsdialogues. we hope that our research will spur the development of dialogue systems that are more proactive and knowledgeable in various scenarios.