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

October 07, 2022 ยท Declared Dead ยท ๐Ÿ› Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

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Authors Andrรฉs Garcรญa-Silva, Cristian Berrรญo, Josรฉ Manuel Gรณmez-Pรฉrez, Josรฉ Antonio Martรญnez-Heras, Alessandro Donati, Ilaria Roma arXiv ID 2210.03422 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 8 Venue Annual International ACM SIGIR Conference on Research and Development in Information Retrieval Last Checked 4 months ago
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.
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