Jets are ubiquitous observables in collider experiments, composed of complex collections of particles that require classification. Over the past decade, machine learning-based classifiers have significantly enhanced our jet tagging capabilities, with increasingly sophisticated models leading to further improvements. This raises a fundamental question: How close are we to the theoretical limit...
Foundation models are a very successful approach to linguistic tasks. Naturally, there is the desire to develop foundation models for physics data. Currently, existing networks are much smaller than publicly available Large Language Models (LLMs), the latter having typically billions of parameters. By applying pretrained LLMs in an unconventional way, we introduce large networks for cosmological data.
