Cited by 102Anomaly Detection Techniques and ApplicationsRobot Manipulation and LearningAdversarial Robustness in Machine Learning

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Semantic anomaly detection with large language models

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Elhafsi, Amine, Sinha, Rohan, Agia, Christopher, Schmerling, Edward, Nesnas, Issa A. D., Pavone, Marco·2023·Autonomous Robots

DOI 10.1007/s10514-023-10132-6

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Authors: Elhafsi, A., Sinha, R., Agia, C., Schmerling, E., Nesnas, I. A. D., & Pavone, M.
Affiliations: Stanford University (US)
Jet Propulsion Laboratory (US)
Corresponding author: Elhafsi, Amine
ORCID: Sinha, Rohan
Agia, Christopher
Schmerling, Edward
Nesnas, Issa A. D.
Pavone, Marco
Venue: Autonomous Robots
Publisher: Springer Science and Business Media LLC
Published: 2023-10-23
Volume: 47
Issue: 8
Pages: 1035-1055
ISSN: 0929-5593 (ISSN-L)
1573-7527
DOI: 10.1007/s10514-023-10132-6
OpenAlex: W4387876242
Cited by: 101
References: 57
Citations by year: 2026: 25 · 2025: 46 · 2024: 29 · 2023: 1
FWCI: 9.52
Type: journal article
Language: en
Open access: green
arxiv.org
Licence: cc-by
www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Autonomous Robots (publishedVersion)
arXiv (Cornell University) (submittedVersion, cc-by)
arXiv (Cornell University) (cc-by)
Funders: National Aeronautics and Space Administration (80NSSC19K1143, 80NSSC20M0163)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
Keywords: semantic anomaly detection, large language models, autonomous driving, object manipulation, anomaly monitoring, foundation models, semantic reasoning

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