LLM embeddings condition a generative transformer to enable faster convergence, better performance, and generalization to unseen LHC processes using a single model.
OmniJet-α: The first cross-task foundation model for particle physics.Machine Learning: Science and Technology, 5:035031, 2024
2 Pith papers cite this work. Polarity classification is still indexing.
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Pretraining data composition can be used to engineer neural scaling laws in hadronic jet classification toward data-heavy rather than model-size-heavy regimes.
citing papers explorer
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One Generator, Any Process: LLM-Conditioning for the LHC
LLM embeddings condition a generative transformer to enable faster convergence, better performance, and generalization to unseen LHC processes using a single model.
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Towards Engineering Scaling Laws with Pretraining Data Composition
Pretraining data composition can be used to engineer neural scaling laws in hadronic jet classification toward data-heavy rather than model-size-heavy regimes.