Felix Grezes

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Felix Grezes studied artificial intelligence and neural networks at the Sorbonne in Paris and the City University in New York, working in the fields of adversarial defenses, binary neural networks for speech recognition, GANs for text data, reservoir computing, audio source separation, acoustic prosody, and computational biology.

He started at NASA/ADS as a Machine Learning and Natural Language Processing specialist in March 2021.

Profile Picture adass-xxxi-2021/question_uploads/fgrezes_qQ9VQe4.jpg Affiliation

The SAO/NASA Astrophysics Data System


Building astroBERT, a language model for Astronomy & Astrophysics.
Felix Grezes

The existing search tools for exploring the NASA Astrophysics Data System (ADS) can be quite rich and empowering (e.g., similar and trending operators), but researchers are not yet allowed to fully leverage semantic search.
For example, a query for "results from the Planck mission" should be able to distinguish between all the various meanings of Planck (person, mission, constant, institutions and more) without further clarification from the user.
At ADS, we are applying modern machine learning and natural language processing techniques to our dataset of recent astronomy publications to train astroBERT, a deeply contextual language model based on research at Google.
Using astroBERT, we aim to enrich the ADS dataset and improve its discoverability, and in particular we are developing our own named entity recognition tool. We present here our preliminary results and lessons learned.

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