Definition
The PAQ (Pseudo-Answer Quality) dataset contains millions of automatically generated question-answer pairs extracted from Wikipedia. It is specifically engineered to train dense retrievers by providing negative samples and positive matches for learning embedding spaces where relevant passages are clustered closely together. This approach significantly improves the efficiency and accuracy of open-domain question answering systems.
Summary
A large-scale dataset of question-answer pairs derived from Wikipedia, designed for dense passage retrieval training.
Key Concepts
- Dense Passage Retrieval
- Negative Sampling
- Open-Domain QA
- Wikipedia Extraction
Use Cases
- Training dense retrievers
- Open-domain question answering
- Benchmarking retrieval performance