@inproceedings{lourie-etal-2025-integrating,
title = "Integrating Semantic and Statistical Features for Authorial Clustering of Qumran Scrolls",
author = "Lourie, Yonatan and
Ben-Dov, Jonathan and
Sharan, Roded",
editor = "Anderson, Adam and
Gordin, Shai and
Li, Bin and
Liu, Yudong and
Passarotti, Marco C. and
Sprugnoli, Rachele",
booktitle = "Proceedings of the Second Workshop on Ancient Language Processing",
month = may,
year = "2025",
address = "The Albuquerque Convention Center, Laguna",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.alp-1.2/",
doi = "10.18653/v1/2025.alp-1.2",
pages = "12--21",
ISBN = "979-8-89176-235-0",
abstract = "We present a novel framework for authorial classification and clustering of the Qumran Dead Sea Scrolls (DSS). Our approach com-bines modern Hebrew BERT embeddings with traditional natural language processing features in a graph neural network (GNN) architecture. Our results outperform baseline methods on both the Dead Sea Scrolls and a validation dataset of the Hebrew Bible. In particular, we leverage our model to provide significant insights into long-standing debates, including the classification of sectarian and non-sectarian texts and the division of the Hodayot collection of hymns."
}
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<abstract>We present a novel framework for authorial classification and clustering of the Qumran Dead Sea Scrolls (DSS). Our approach com-bines modern Hebrew BERT embeddings with traditional natural language processing features in a graph neural network (GNN) architecture. Our results outperform baseline methods on both the Dead Sea Scrolls and a validation dataset of the Hebrew Bible. In particular, we leverage our model to provide significant insights into long-standing debates, including the classification of sectarian and non-sectarian texts and the division of the Hodayot collection of hymns.</abstract>
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%0 Conference Proceedings
%T Integrating Semantic and Statistical Features for Authorial Clustering of Qumran Scrolls
%A Lourie, Yonatan
%A Ben-Dov, Jonathan
%A Sharan, Roded
%Y Anderson, Adam
%Y Gordin, Shai
%Y Li, Bin
%Y Liu, Yudong
%Y Passarotti, Marco C.
%Y Sprugnoli, Rachele
%S Proceedings of the Second Workshop on Ancient Language Processing
%D 2025
%8 May
%I Association for Computational Linguistics
%C The Albuquerque Convention Center, Laguna
%@ 979-8-89176-235-0
%F lourie-etal-2025-integrating
%X We present a novel framework for authorial classification and clustering of the Qumran Dead Sea Scrolls (DSS). Our approach com-bines modern Hebrew BERT embeddings with traditional natural language processing features in a graph neural network (GNN) architecture. Our results outperform baseline methods on both the Dead Sea Scrolls and a validation dataset of the Hebrew Bible. In particular, we leverage our model to provide significant insights into long-standing debates, including the classification of sectarian and non-sectarian texts and the division of the Hodayot collection of hymns.
%R 10.18653/v1/2025.alp-1.2
%U https://aclanthology.org/2025.alp-1.2/
%U https://doi.org/10.18653/v1/2025.alp-1.2
%P 12-21
Markdown (Informal)
[Integrating Semantic and Statistical Features for Authorial Clustering of Qumran Scrolls](https://aclanthology.org/2025.alp-1.2/) (Lourie et al., ALP 2025)
ACL