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Dialogue Understanding datasets
archive 2025-07-28
9 datasets carry the task tag "Dialogue Understanding" (the task itself: Dialogue Understanding), ordered by the archive's paper count. Page 1 of 1: 9 shown of 9. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
Dialogue Understanding datasets 1–9 of 9
Doc2Dial (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.
36 papers · 0 benchmarks
A machine reading comprehension (MRC) dataset with discourse structure built over multiparty dialog.
29 papers · 2 benchmarks
Most existing dialogue systems fail to respond properly to potentially unsafe user utterances by either ignoring or passively agreeing with them.
13 papers · 1 benchmark
In MutualFriends, two agents, A and B, each have a private knowledge base, which contains a list of friends with multiple attributes (e.g., name, school, major, etc.).
7 papers · 0 benchmarks
DiaASQ (Conversational Aspect-based Sentiment Quadruple Extraction)
DiaASQ is a fine-grained Aspect-based Sentiment Analysis (ABSA) benchmark under the conversation scenario.
4 papers · 2 benchmarks
Emotional Dialogue Acts data contains dialogue act labels for existing emotion multi-modal conversational datasets.
3 papers · 0 benchmarks
WDC-Dialogue is a dataset built from the Chinese social media to train EVA.
3 papers · 0 benchmarks
Harry Potter Dialogue is the first dialogue dataset that integrates with scene, attributes and relations which are dynamically changed as the storyline goes on.
1 paper · 2 benchmarks
The Mafia Dataset was created to model the behavior of deceptive actors in the context of the Mafia game, as described in the paper “Putting the Con in Context: Identifying Deceptive Actors in the Game of Mafia”.
1 paper · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.