BERT-based Authorship Attribution on the Romanian Dataset called ROST
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Abstract (arXiv)
Being around for decades, the problem of Authorship Attribution is still very much in focus currently. Some of the more recent instruments used are the pre-trained language models, the most prevalent being BERT. Here we used such a model to detect the authorship of texts written in the Romanian language. The dataset used is highly unbalanced, i.e., significant differences in the number of texts per author, the sources from which the texts were collected, the time period in which the authors lived and wrote these texts, the medium intended to be read (i.e., paper or online), and the type of writing (i.e., stories, short stories, fairy tales, novels, literary articles, and sketches). The results are better than expected, sometimes exceeding 87% macro-accuracy.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 12 of its 47 references that are in the map. First posted on arXiv 29 Jan 2023.
Builds on
12 of 47 references.
References · 12
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- 2020The birth of Romanian BERTcited by 44
- 2022On the State of the Art in Authorship Attribution and Authorship Verificationcited by 27
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- 2021The Topic Confusion Task: A Novel Scenario for Authorship Attributioncited by 17
- 2015Author Identification using Multi-headed Recurrent Neural Networkscited by 13
- 2022A comparison of several AI techniques for authorship attribution on Romanian textscited by 4
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.