Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval

Wenhan Xiong, Xiang Li, Srini Iyer, Jingfei Du, Patrick Lewis, William Yang Wang, Yashar Mehdad, Scott Yih, Sebastian Riedel, Douwe Kiela, Barlas Oguz

Keywords: multi-hop question answering, recursive dense retrieval, open domain complex question answering

Abstract: We propose a simple and efficient multi-hop dense retrieval approach for answering complex open-domain questions, which achieves state-of-the-art performance on two multi-hop datasets, HotpotQA and multi-evidence FEVER. Contrary to previous work, our method does not require access to any corpus-specific information, such as inter-document hyperlinks or human-annotated entity markers, and can be applied to any unstructured text corpus. Our system also yields a much better efficiency-accuracy trade-off, matching the best published accuracy on HotpotQA while being 10 times faster at inference time.

One-sentence Summary: We propose a simple yet effective multi-hop dense retrieval approach for answering complex open-domain questions.

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Code: [ facebookresearch/multihop_dense_retrieval](https://github.com/facebookresearch/multihop_dense_retrieval)

Data: [HotpotQA](https://paperswithcode.com/dataset/hotpotqa), [Natural Questions](https://paperswithcode.com/dataset/natural-questions)

Community Implementations: [ 1 code implementation](https://www.catalyzex.com/paper/arxiv:2009.12756/code)