Challenge: Existing approaches to discriminate between inherited and borrowed Latin words have been used to investigate the problem of automatic discrimination between a language's sound shifts.
Approach: They propose a new dataset to investigate the problem of automatically discriminating between inherited and borrowed Latin words in Romance languages.
Outcome: The proposed model can automatically discriminate between inherited and borrowed Latin words on two versions of the dataset, orthographic and phonetic.

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Challenge: Existing methods for discriminating between cognates and borrowings are difficult, but they provide a deeper insight into the history of a language and allow for a better characterization of language relatedness.
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Detecting Lexical Borrowings from Dominant Languages in Multilingual Wordlists (2023.eacl-main)

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Challenge: Language contact is reflected in the transfer of words from donor to recipient languages.
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A Generalized Method for Automated Multilingual Loanword Detection (2022.coling-1)

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Challenge: Loanwords are words incorporated from one language into another without translation . authors present a method to automatically detect loanwords across language pairs .
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Verba volant, scripta volant? Don’t worry! There are computational solutions for protoword reconstruction (2024.emnlp-main)

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Challenge: Existing methods for protoword reconstruction are limited to a few languages.
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Ab Initio: Automatic Latin Proto-word Reconstruction (C18-1)

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Challenge: Existing methods for proto-word reconstruction are time-consuming and manual, but few studies have done it . a recent study used cognates to reconstruct ancient languages from their modern counterparts .
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RoBoCoP: A Comprehensive ROmance BOrrowing COgnate Package and Benchmark for Multilingual Cognate Identification (2023.emnlp-main)

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Challenge: Existing databases for romance cognates are scattered, incomplete, noisy, or have uncertain availability.
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Friend or Foe? A Computational Investigation of Semantic False Friends across Romance Languages (2025.emnlp-main)

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Challenge: lexical divergence between cognate and borrowings is studied in the five Romance languages.
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It takes two to borrow: a donor and a recipient. Who’s who? (2024.findings-acl)

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Challenge: Existing methods for identifying the direction of borrowing are limited.
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Sequence Models for Computational Etymology of Borrowings (2021.findings-acl)

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Challenge: a computational model of word borrowing can be useful for lexicon expansion and language preservation.
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ConLoan: A Contrastive Multilingual Dataset for Evaluating Loanwords (2025.acl-long)

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Challenge: Lexical borrowing is a ubiquitous linguistic phenomenon influenced by geopolitical, societal, and technological factors.
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