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@ARTICLE{Hayrapetyan:643085,
      author       = {Hayrapetyan, Aram and others},
      collaboration = {{CMS Collaboration}},
      title        = {{M}achine-learning techniques for model-independent
                      searches in dijet final states},
      reportid     = {PUBDB-2025-05829, arXiv:2512.20395. CMS-MLG-23-002.
                      CERN-EP-2025-269},
      year         = {2025},
      note         = {Submitted to Machine Learning: Science and Technology. All
                      figures and tables can be found at
                      http://cms-results.web.cern.ch/cms-results/public-results/publications/MLG-23-002
                      (CMS Public Pages)},
      abstract     = {Anomaly detection methods used in a recent search for new
                      phenomena by CMS at the CERN LHC are presented. The methods
                      use machine learning to detect anomalous jets produced in
                      the decay of new massive particles. The effectiveness of
                      these approaches in enhancing sensitivity to various signals
                      is studied and compared using data collected in
                      proton-proton collisions at a center-of-mass energy of 13
                      TeV. In an example analysis, the capabilities of anomaly
                      detection methods are further demonstrated by identifying
                      large-radius jets consistent with Lorentz-boosted
                      hadronically decaying top quarks in a model-agnostic
                      framework.},
      cin          = {CMS},
      cid          = {I:(DE-H253)CMS-20120731},
      pnm          = {611 - Fundamental Particles and Forces (POF4-611) / DFG
                      project G:(GEPRIS)390833306 - EXC 2121: Das Quantisierte
                      Universum II (390833306) / HIDSS-0002 - DASHH: Data Science
                      in Hamburg - Helmholtz Graduate School for the Structure of
                      Matter $(2019_IVF-HIDSS-0002)$},
      pid          = {G:(DE-HGF)POF4-611 / G:(GEPRIS)390833306 /
                      $G:(DE-HGF)2019_IVF-HIDSS-0002$},
      experiment   = {EXP:(DE-H253)LHC-Exp-CMS-20150101},
      typ          = {PUB:(DE-HGF)25},
      eprint       = {2512.20395},
      howpublished = {arXiv:2512.20395},
      archivePrefix = {arXiv},
      SLACcitation = {$\%\%CITATION$ = $arXiv:2512.20395;\%\%$},
      doi          = {10.3204/PUBDB-2025-05829},
      url          = {https://bib-pubdb1.desy.de/record/643085},
}