Conveners
🔀 Foundation Models
- Lorenzo Moneta (CERN)
🔀 Foundation Models
- Daniele Bonacorsi (Istituto Nazionale di Fisica Nucleare)
-
Sascha Caron6/17/25, 2:15 PMFoundation ModelsParallel talk
This work explores ideas and provides a potential roadmap for the development and evaluation of physics-specific large-scale AI models, which we call Large Physics Models (LPMs). These models, based on foundation models such as Large Language Models (LLMs) - trained on broad data - are tailored to address the demands of physics research. LPMs can function independently or as part of an...
Go to contribution page -
Ke Li6/17/25, 2:35 PMFoundation ModelsParallel talk
The data processing and analyzing is one of the main challenges at HEP experiments, normally one physics result can take more than 3 years to be conducted. To accelerate the physics analysis and drive new physics discovery, the rapidly developing Large Language Model (LLM) is the most promising approach, it have demonstrated astonishing capabilities in recognition and generation of text while...
Go to contribution page -
Dr Dmitriy Kostunin (DESY)6/17/25, 2:55 PMFoundation ModelsPoster Session A
We develop AI agents based on instruction-finetuned large language models (LLMs) to assist in the engineering and operation of the Cherenkov Telescope Array Observatory (CTAO) Control and Data Acquisition Software (ACADA). These agents align with project-specific documentation and codebases, understand contextual information, interact with external APIs, and communicate with users in natural...
Go to contribution page -
Yong Sheng Koay (Uppsala University)6/17/25, 2:58 PMFoundation ModelsPoster Session A
In physics, Lagrangians provide a systematic way to describe laws governing physical systems. In the context of particle physics, they encode the interactions and behavior of the fundamental building blocks of our universe. By treating Lagrangians as complex, rule-based constructs similar to linguistic expressions, we trained a transformer model-- proven to be effective in natural language...
Go to contribution page -
Waleed Esmail (University of Münster)6/17/25, 3:01 PMFoundation ModelsPoster Session A
We introduce a SeismoGPT, a foundation model for seismology that leverages transformer-based architectures to model seismic waveforms. Inspired by natural language processing techniques. This approach tokenizes continuous seismograms by dividing them into fixed-length patches, where each patch represents a sequence of waveform samples. These patches serve as input tokens to the transformer...
Go to contribution page -
Dr Quentin Führing (Lamarr Institute for Machine Learning and Artificial Intelligence, Dortmund, Germany)6/18/25, 4:30 PMFoundation ModelsPoster Session B
Measurements of neutral, oscillating mesons are a gateway to quantum mechanics and give access to the fundamental interactions of elementary particles. For example, precise measurements of $CP$ violation in neutral $B$ mesons can be taken in order to test the Standard Model of particle physics. These measurements require knowledge of the $B$-meson flavour at the time of its production, which...
Go to contribution page -
Marta Ewelina Babicz (University of Zurich)6/18/25, 4:33 PMPatterns & AnomaliesPoster Session B
The LEGEND experiment searches for neutrinoless double beta decay (0νββ) using high-purity germanium (HPGe) detectors enriched in 7676Ge, where minimizing backgrounds is essential for improving discovery sensitivity. A key technique for this is pulse shape discrimination (PSD), traditionally done using A/E-based cuts that exploit differences in current pulse morphology. However, such methods...
Go to contribution page -
Ayodele Ore (Heidelberg University, ITP)6/18/25, 4:36 PMFoundation ModelsParallel talk
The Square Kilometer Array (SKA) will bring about a new era of radio astronomy by allowing 3D imaging of the Universe during Cosmic Dawn and Reionization. Machine learning promises to be a powerful tool to analyze the highly structured and complex signal, however accurate training datasets are expensive to simulate and supervised learning may not generalize. We introduce SKATR, a...
Go to contribution page -
Jan Steinheimer-Froschauer (Frankfurt Institute for Advanced Studies)6/18/25, 4:56 PMOtherParallel talk
In 2020, the German ministry of education and research launched an action plan to advance digitization in basic research. Alongside the plan a line of funding (ErUM-Data) was established to support interdisciplinary joint consortia that focus on progressing this process with concrete research projects. At the same time funding was allocated for the ErUM-Data HUB, as a networking and transfer...
Go to contribution page