InCa and InDia: Inline Casing and Diacritization Preprocessing For Robust-to-Noise Tokenization and Interpretability
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10511651" target="_blank" >RIV/00216208:11320/25:10511651 - isvavai.cz</a>
Result on the web
<a href="https://openreview.net/pdf?id=9GwVWxjVmN" target="_blank" >https://openreview.net/pdf?id=9GwVWxjVmN</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
InCa and InDia: Inline Casing and Diacritization Preprocessing For Robust-to-Noise Tokenization and Interpretability
Original language description
We introduce two inline approaches to tokenization preprocessing of casing (InCa) and diacritics (InDia) in the texts. Their main component relies on an automatically created external dictionary that stores information about the most frequent casings or diacritizations of words, and marking only the non-frequent spellings. We show that in a number of noising scenarios, our casing algorithm shows the best performance, and in the cases where it performs on par with the alternative solutions, the intrinsic parameters of the tokenizer trained on our data are more stable. As for inline diacritization, this is the first solution of that type to our knowledge; we show its improvement on robustness against the de-diacritized texts compared to tokenization without preprocessing. We share our preprocessing systems at a public GitHub repository.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA25-16242S" target="_blank" >GA25-16242S: Better Tokenization for Multilingual Language Models and Machine Translation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů