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    <abstract>Recent advancements in Large Language models (LLMs) have empowered them to achieve text generation capabilities on par with those of humans. These recent advances paired with the wide availability of those models have made Large Language models adaptable in many domains, from scientific writing to story generation along with many others. This recent rise has made it crucial to develop systems to discriminate between human-authored and synthetic text generated by Large Language models (LLMs). Our proposed system for the ALTA shared task, based on ensembling a number of language models, claimed first place on the development set with an accuracy of 99.35% and third place on the test set with an accuracy of 98.35%.</abstract>
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%0 Conference Proceedings
%T An Ensemble Based Approach To Detecting LLM-Generated Texts
%A El-Sayed, Ahmed
%A Nasr, Omar
%Y Muresan, Smaranda
%Y Chen, Vivian
%Y Casey, Kennington
%Y David, Vandyke
%Y Nina, Dethlefs
%Y Koji, Inoue
%Y Erik, Ekstedt
%Y Stefan, Ultes
%S Proceedings of the 21st Annual Workshop of the Australasian Language Technology Association
%D 2023
%8 November
%I Association for Computational Linguistics
%C Melbourne, Australia
%F el-sayed-nasr-2023-ensemble
%X Recent advancements in Large Language models (LLMs) have empowered them to achieve text generation capabilities on par with those of humans. These recent advances paired with the wide availability of those models have made Large Language models adaptable in many domains, from scientific writing to story generation along with many others. This recent rise has made it crucial to develop systems to discriminate between human-authored and synthetic text generated by Large Language models (LLMs). Our proposed system for the ALTA shared task, based on ensembling a number of language models, claimed first place on the development set with an accuracy of 99.35% and third place on the test set with an accuracy of 98.35%.
%U https://aclanthology.org/2023.alta-1.20
%P 164-168

Markdown (Informal)

[An Ensemble Based Approach To Detecting LLM-Generated Texts](https://aclanthology.org/2023.alta-1.20) (El-Sayed & Nasr, ALTA 2023)

• An Ensemble Based Approach To Detecting LLM-Generated Texts (El-Sayed & Nasr, ALTA 2023)

ACL

• Ahmed El-Sayed and Omar Nasr. 2023. An Ensemble Based Approach To Detecting LLM-Generated Texts. In Proceedings of the 21st Annual Workshop of the Australasian Language Technology Association, pages 164–168, Melbourne, Australia. Association for Computational Linguistics.