  We propose MultiDoc2Dial, a new task and dataset on modeling goal-oriented
dialogues grounded in multiple documents. Most previous works treat
document-grounded dialogue modeling as a machine reading comprehension task
based on a single given document or passage. In this work, we aim to address
more realistic scenarios where a goal-oriented information-seeking conversation
involves multiple topics, and hence is grounded on different documents. To
facilitate such a task, we introduce a new dataset that contains dialogues
grounded in multiple documents from four different domains. We also explore
modeling the dialogue-based and document-based context in the dataset. We
present strong baseline approaches and various experimental results, aiming to
support further research efforts on such a task.
