Pruning the Index Contents for Memory Efficient Open-Domain QA

Martin Fajcik; Martin Docekal; Karel Ondrej; Pavel Smrz

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arXiv · 2102.10697

Pruning the Index Contents for Memory Efficient Open-Domain QA

Martin Fajcik·Martin Docekal·Karel Ondrej·Pavel Smrz

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Abstract

This work presents a novel pipeline that demonstrates what is achievable with a combined effort of state-of-the-art approaches. Specifically, it proposes the novel R2-D2 (Rank twice, reaD twice) pipeline composed of retriever, passage reranker, extractive reader, generative reader and a simple way to combine them. Furthermore, previous work often comes with a massive index of external documents that scales in the order of tens of GiB. This work presents a simple approach for pruning the contents of a massive index such that the open-domain QA system altogether with index, OS, and library components fits into 6GiB docker image while retaining only 8% of original index contents and losing only 3% EM accuracy.

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BibTeX RIS

Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz. 2021-02-21. Pruning the Index Contents for Memory Efficient Open-Domain QA. https://arxiv.org/abs/2102.10697

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