This repository is for reproducing MDR results on the ConcurrentQA benchmark with and without the PAIR framework as in this paper: Reasoning over Public and Private Data in Retrieval-Based Systems. The instructions to set up the environment, download data, and execute the training and evaluation scripts are detailed in the ConcurrentQA Repository.
MDR is a simple and generalized dense retrieval method which recursively retrieves supporting text passages for answering complex open-domain questions. The repo provides code and pretrained retrieval models that produce state-of-the-art retrieval performance on two multi-hop QA datasets (the HotpotQA dataset and the multi-hop subset of the FEVER fact extraction and verification dataset).
See their ICLR paper for additional details: Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval
Please also cite the following if you use this code.
@article{xiong2020answering,
title={Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval},
author={Xiong, Wenhan and Li, Xiang Lorraine and Iyer, Srinivasan and Du, Jingfei and Lewis, Patrick and Wang, William Yang and Mehdad, Yashar and Yih, Wen-tau and Riedel, Sebastian and Kiela, Douwe and O{\u{g}}uz, Barlas},
journal={International Conference on Learning Representations},
year={2021}
}
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