Is tokenization needed for masked particle modeling?

In this work, we significantly enhance masked particle modeling (MPM), a self-supervised learning scheme for constructing highly expressive representations of unordered sets relevant to developing foundation models for high-energy physics. In MPM, a model is trained to recover the missing elements o...

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Bibliographic Details
Main Authors: Matthew Leigh, Samuel Klein, François Charton, Tobias Golling, Lukas Heinrich, Michael Kagan, Inês Ochoa, Margarita Osadchy
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Machine Learning: Science and Technology
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Online Access:https://doi.org/10.1088/2632-2153/addb98
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