Journals of Accelerator Conferences Website (JACoW)

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URLhttps://doi.org/10.18429/JACoW-IPAC2025-THPM023
TitleThe journey towards a specialized text embedding model for accelerator physics
Authors
  • T. Hellert, A. Pollastro, J. Montenegro, M. Venturini
    Lawrence Berkeley National Laboratory
AbstractWe present PhysBERT and AccPhysBERT, specialized sentence-embedding models trained on 1.2 million arXiv physics papers and fine-tuned for accelerator physics, respectively. Evaluation across retrieval, clustering, and similarity tasks shows gains of up to 12\% over general-purpose models for physics corpora and 18\% for accelerator-specific tasks. Applications include semantic reviewer–paper matching, Retrieval-Augmented Generation for control-room logbooks, and rapid sub-domain adaptation. We analyze key design choices—data curation, masking objectives, and contrastive fine-tuning—and outline strategies for continual adaptation, providing a blueprint for domain-specific embeddings in the physical sciences.
Paperdownload: THPM023.pdf
CiteBibTeX, LaTeX, Text/Word, RIS, EndNote
Conference16th International Particle Accelerator Conference
Series
LocationTaipei, Taiwan
Date01-06 Jun 2025
PublisherJACoW Publishing, Geneva, Switzerland
Editorial Board* Ming-Chyuan Lin - National Synchrotron Radiation Research Center * Yoichi Sato - KEK * Jui-Che Huang - National Synchrotron Radiation Research Center * David Button - Australian Nuclear Science and Technology Organisation * Ping-Shun Chuang - National Synchrotron Radiation Research Center
Online ISBN978-3-95450-248-6
Online ISSN2673-5490
Received30 May 2025
Revised05 June 2025
Accepted05 June 2025
Issued05 November 2025
DOI10.18429/JACoW-IPAC2025-THPM023
Pages2730-2732