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Conversational Question Answering datasets
archive 2025-07-28
10 datasets carry the task tag "Conversational Question Answering" (the task itself: Conversational Question Answering), ordered by the archive's paper count. Page 1 of 1: 10 shown of 10. 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
Conversational Question Answering datasets 1–10 of 10
CoQA (Conversational Question Answering Challenge)
CoQA is a large-scale dataset for building Conversational Question Answering systems.
281 papers · 2 benchmarks
QuAC (Question Answering in Context)
Question Answering in Context is a large-scale dataset that consists of around 14K crowdsourced Question Answering dialogs with 98K question-answer pairs in total.
178 papers · 1 benchmark
CANARD (A Dataset for Question-in-Context Rewriting)
CANARD is a dataset for question-in-context rewriting that consists of questions each given in a dialog context together with a context-independent rewriting of the question.
58 papers · 1 benchmark
ConvFinQA (Conversational Finance Question Answering)
ConvFinQA is a dataset designed to study the chain of numerical reasoning in conversational question answering.
38 papers · 2 benchmarks
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
MultiDoc2Dial (MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documents)
MultiDoc2Dial is a new task and dataset on modeling goal-oriented dialogues grounded in multiple documents.
26 papers · 0 benchmarks
A dataset with 2,437 dialogues and 10,917 QA pairs.
18 papers · 0 benchmarks
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
1 paper · 0 benchmarks
UIT-ViCoQA (Conversational machine reading comprehension in the Vietnamese language)
UIT-ViCoQA is a new corpus for conversational machine reading comprehension in the Vietnamese language.
1 paper · 0 benchmarks
Dataset for our paper Disambiguation-Centric Finetuning Makes Enterprise Tool-Calling LLMs More Realistic and Less Risky which includes 5000 enterprise tools and the corresponding dialogues generated using DiaFORGE UTC data engine.
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.