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.
@article{arxiv.2109.12595,
title = {MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documents},
author = {Song Feng and Siva Sankalp Patel and Hui Wan and Sachindra Joshi},
journal= {arXiv preprint arXiv:2109.12595},
year = {2022}
}