Jonathan Prada


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Embedding-based Scientific Literature Discovery in a Text Editor Application
Onur Gökçe | Jonathan Prada | Nikola I. Nikolov | Nianlong Gu | Richard H.R. Hahnloser
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

Each claim in a research paper requires all relevant prior knowledge to be discovered, assimilated, and appropriately cited. However, despite the availability of powerful search engines and sophisticated text editing software, discovering relevant papers and integrating the knowledge into a manuscript remain complex tasks associated with high cognitive load. To define comprehensive search queries requires strong motivation from authors, irrespective of their familiarity with the research field. Moreover, switching between independent applications for literature discovery, bibliography management, reading papers, and writing text burdens authors further and interrupts their creative process. Here, we present a web application that combines text editing and literature discovery in an interactive user interface. The application is equipped with a search engine that couples Boolean keyword filtering with nearest neighbor search over text embeddings, providing a discovery experience tuned to an author’s manuscript and his interests. Our application aims to take a step towards more enjoyable and effortless academic writing. The demo of the application ( and a short video tutorial ( are available online.