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.
MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documents
A new task and dataset, MultiDoc2Dial, facilitate modeling goal-oriented dialogues using multiple documents, presenting strong baseline approaches and experimental results.
- Year
- 2021
- Venue
- EMNLP 2021 11
- Authors
- 4
- Hosting
- Abstract onlyARXIV-DEFAULT
Cite
Notes
Only stored in your browser.
Attribution
- Abstract & full text
- arxiv.org/abs/2109.12595ARXIV-DEFAULT
- TL;DR
- Semantic Scholar