{"url":"/dataset/multidoc2dial","name":"MultiDoc2Dial","full_name":"MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documents","description_markdown":"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.","description_withheld":null,"homepage":"https://doc2dial.github.io/multidoc2dial/","introduced_date":"2021-09-26","introduced_date_note":null,"introduced_by":{"paper":"/paper/multidoc2dial-modeling-dialogues-grounded-in","title":"MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documents","first_author":"Song Feng","url":null},"license":{"name":"Apache-2.0 License","url":"https://github.com/IBM/multidoc2dial/blob/main/LICENSE"},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Question Answering","url":"/task/question-answering","datasets_with_task":"/datasets/task/question-answering"},{"name":"Dialogue Generation","url":"/task/dialogue-generation","datasets_with_task":"/datasets/task/dialogue-generation"},{"name":"Open-Domain Dialog","url":"/task/open-domain-dialog","datasets_with_task":"/datasets/task/open-domain-dialog"},{"name":"Conversational Question Answering","url":"/task/conversational-question-answering","datasets_with_task":"/datasets/task/conversational-question-answering"},{"name":"Goal-Oriented Dialogue Systems","url":"/task/goal-oriented-dialogue-systems","datasets_with_task":"/datasets/task/goal-oriented-dialogue-systems"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["MultiDoc2Dial"],"data_loaders":[{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/IBM/multidoc2dial","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/multidoc2dial","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/IBM/multidoc2dial","url":"https://github.com/IBM/multidoc2dial","frameworks":["pytorch"]}],"num_papers_in_archive":26,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}