Search Results for author: Paul Darm

Found 2 papers, 1 papers with code

FloodBrain: Flood Disaster Reporting by Web-based Retrieval Augmented Generation with an LLM

no code implementations5 Nov 2023 Grace Colverd, Paul Darm, Leonard Silverberg, Noah Kasmanoff

With our tool, we aim to advance the use of LLMs for disaster impact reporting and reduce the time for coordination of humanitarian efforts in the wake of flood disasters.

Humanitarian Question Answering +2

Knowledge Base Question Answering for Space Debris Queries

1 code implementation31 May 2023 Paul Darm, Antonio Valerio Miceli-Barone, Shay B. Cohen, Annalisa Riccardi

In this work we present a system, developed for the European Space Agency (ESA), that can answer complex natural language queries, to support engineers in accessing the information contained in a KB that models the orbital space debris environment.

Knowledge Base Question Answering Natural Language Queries

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