Omkar2118/datasets huggingface dataset:
MultiDoc2Dial
Full name: MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documents

MultiDoc2Dial is 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. We aim to address more realistic scenarios where a goal-oriented information-seeking conversation involves multiple topics, and hence is grounded on different documents.

Introducing paper: MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documents
Doc2Dial
Full name: Doc2Dial: Document-grounded Dialogue

For goal-oriented document-grounded dialogs, it often involves complex contexts for identifying the most relevant information, which requires better understanding of the inter-relations between conversations and documents. Meanwhile, many online user-oriented documents use both semi-structured and unstructured contents for guiding users to access information of different contexts. Thus, we create a new goal-oriented document-grounded dialogue dataset that captures more diverse scenarios derived from various document contents from multiple domains such ssa.gov and studentaid.gov. For data collection, we propose a novel pipeline approach for dialogue data construction, which has been adapted and evaluated for several domains.

Introducing paper: doc2dial: A Goal-Oriented Document-Grounded Dialogue Dataset