Papers with Crawl Question Answering dataset

1 papers
CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training (2022.findings-naacl)

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Challenge: Existing approaches to answer open domain questions rely on unlabeled text or synthetically generated question-answer pairs.
Approach: They propose a large-scale open-domain question-answering dataset based on the Common Crawl project that can be used to in-domain pre-train popular language models.
Outcome: The proposed dataset achieves promising results in zero-shot, low resource and fine-tuned settings across multiple tasks, models and benchmarks.

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