29 citations · 42 across the 8 of their papers we have counts for
3 papers · 1 filter
Enhancing next token prediction based pre-training for jet foundation models
Joschka Birk, Anna Hallin, Gregor Kasieczka +3
Next token prediction is an attractive pre-training task for jet foundation models, in that it is simulation free and enables excellent generative capabilities that can transfer ac…
Reconstructing hadronically decaying tau leptons with a jet foundation model
Laurits Tani, Joosep Pata, Joschka Birk
The limited availability and accuracy of simulated data has motivated the use of foundation models in high energy physics, with the idea to first train a task-agnostic model on lar…
OmniJet-: Learning point cloud calorimeter simulations using generative transformers
Joschka Birk, Frank Gaede, Anna Hallin +3
We show the first use of generative transformers for generating calorimeter showers as point clouds in a high-granularity calorimeter. Using the tokenizer and generative part of th…