Physics Event Classification Using Large Language Models
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Abstract (arXiv)
The 2023 AI4EIC hackathon was the culmination of the third annual AI4EIC workshop at The Catholic University of America. This workshop brought together researchers from physics, data science and computer science to discuss the latest developments in Artificial Intelligence (AI) and Machine Learning (ML) for the Electron Ion Collider (EIC), including applications for detectors, accelerators, and experimental control. The hackathon, held on the final day of the workshop, involved using a chatbot powered by a Large Language Model, ChatGPT-3.5, to train a binary classifier neutrons and photons in simulated data from the textscGlueX Barrel Calorimeter. In total, six teams of up to four participants from all over the world took part in this intense educational and research event. This article highlights the hackathon challenge, the resources and methodology used, and the results and insights gained from analyzing physics data using the most cutting-edge tools in AI/ML.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 6 of its 15 references that are in the map. First posted on arXiv 5 Apr 2024.
Builds on
6 of 15 references.
References · 6
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,120
- 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
- 2023Learning to Retrieve In-Context Examples for Large Language Modelscited by 60
- 2022"Flux+Mutability": A Conditional Generative Approach to One-Class Classification and Anomaly Detectioncited by 7
- 2023Artificial Intelligence for the Electron Ion Collider (AI4EIC)cited by 3
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