0

SpaceQA: Answering Questions about the Design of Space Missions and Space Craft Concepts

SpaceQA is an open-domain QA system for space mission design that uses a dense retriever and neural reader with transfer learning, demonstrating effectiveness through ESA evaluation.

Year
2022
Venue
arXiv 2022
Authors
6
Hosting
Abstract onlyARXIV-DEFAULT

Cite

Notes

Only stored in your browser.

Attribution

Abstract & full text
arxiv.org/abs/2210.03422v2ARXIV-DEFAULT
TL;DR
Semantic Scholar
Attribution policy →

Abstract

We present SpaceQA, to the best of our knowledge the first open-domain QA system in Space mission design. SpaceQA is part of an initiative by the European Space Agency (ESA) to facilitate the access, sharing and reuse of information about Space mission design within the agency and with the public. We adopt a state-of-the-art architecture consisting of a dense retriever and a neural reader and opt for an approach based on transfer learning rather than fine-tuning due to the lack of domain-specific annotated data. Our evaluation on a test set produced by ESA is largely consistent with the results originally reported by the evaluated retrievers and confirms the need of fine tuning for reading comprehension. As of writing this paper, ESA is piloting SpaceQA internally.

Authors

6