Dense passage retriever (DPR) is a dense retrieval method described in the following paper:
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, Wen-tau Yih. Dense Passage Retrieval for Open-Domain Question Answering. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769-6781, 2020.
We have trained our own DPR models with our Wikipedia corpus variants using the Tevatron library.
Our own efforts are described in the paper entitled:
Pre-Processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering.
This is the passage encoder portion of a 2nd iteration DPR model for the wiki-text-6-3 corpus variant trained on the amalgamation of the NQ, TriviaQA, WQ, and CuratedTREC datasets.
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