2022/10/07 by Andrés García-Silva, García-Silva, Andrés, Cristian Berrío +9
Computer Science · Engineering · #AI-based Problem Solving and Planning #Advanced Data Processing Techniques #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Oil and Gas Production Techniques
paper · pdf · doi:10.48550/arxiv.2210.03422
openalex publication_date 2022/10/07 · openalex created_date 2022/10/11 · openalex updated_date 2026/07/28
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.