QuAC
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About
QuAC (Question Answering in Context) is a research dataset designed for developing models capable of understanding and participating in information-seeking dialogs. The data consists of interactive dialogs where a student asks freeform questions about a hidden Wikipedia text, and a teacher responds using short excerpts (spans) from the text. QuAC introduces challenges like open-ended, unanswerable questions, and context-dependent questions, distinguishing it from existing machine comprehension datasets. It provides training and validation sets, an evaluation script, and baseline models via AllenNLP, encouraging competitive model submission via CodaLab. Note: The creators emphasize that QuAC is an academic resource with significant limitations and advise reading the datasheet before practical application.
Platform
Features
• hidden test set submission via codalab
• baseline models available via allennlp
• official evaluation script provided
• training and validation sets available for download
• includes unanswerable questions
• span-based evaluation protocol
• interactive dialog structure
• question answering in context dataset
FAQs
What is QuAC?
QuAC (Question Answering in Context) is a dataset for modeling, understanding, and participating in information seeking dialog based on interactive Q&A sessions.
Is QuAC exactly like SQuAD 2.0?
No, QuAC shares principles like span-based evaluation and unanswerable questions but incorporates a new dialog component for interactive information seeking.
How do I get the duck in my paper?
Download the daffyhand.pdf file and use the provided LaTeX macro command \daffy in your document to include the duck image.
Should I use QuAC for practical applications?
QuAC is primarily an academic resource with significant limitations; users must read the detailed datasheet before considering it for any practical application.
Pricing Plans
Free/Academic Use
Free Plan• Full access to Training Set
• Full access to Validation Set
• Evaluation script included
• CC BY-SA 4.0 license
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