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Pretrained jet foundation model successfully utilized for tau reconstruction

Simulating data in particle physics is expensive and not perfectly accurate. To get around this, researchers are now exploring the use of foundation models—large AI models trained in a general, task-agnostic way on large amounts of data.

Just like how language models can be pretrained on the full dataset of internet text before being fine-tuned for specific tasks, these models can learn from large datasets of particle jets, even without labels.

After the pretraining, they can be fine-tuned to solve specific problems using much less data than traditional approaches.

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