Papers with masked language modelling task

2 papers
Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach (2021.emnlp-main)

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Challenge: cuneiform clay tablets were written in 2500 BCE - 100 CE and are a target of extensive transcription and transliteration efforts due to their deterioration.
Approach: They propose to use a masked language modelling task to complete missing text given cuneiform clay tablets written on cuniform signswedges (2500 BCE - 100 CE) they develop models which automatically complete these missing signs based on contextual cues and greedy decoding schemes.
Outcome: The proposed models perform well on missing token prediction (89% hit@5) despite data scarcity (1M tokens), and human evaluations show that they are able to transcribe texts in extinct languages.
To Split or Not to Split: Composing Compounds in Contextual Vector Spaces (2023.emnlp-main)

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Challenge: Contextual word embedding models rely on sub-word tokenization to represent single orthographic words but are often suboptimal in under-resourced contexts.
Approach: They propose to use a masked language modelling task to evaluate the model's performance . they use re-trained tokenizers to pre-split compounds into constituents .
Outcome: The proposed models improve on the masked language modelling task and compositionality prediction by pre-splitting compounds into constituents.

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