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- W4385718093 abstract "How does the word analogy task fit in the modern NLP landscape? Given the rarity of comparable multilingual benchmarks and the lack of a consensual evaluation protocol for contextual models, this remains an open question. In this paper, we introduce MATS: a multilingual analogy dataset, covering forty analogical relations in six languages, and evaluate human as well as static and contextual embedding performances on the task. We find that not all analogical relations are equally straightforward for humans, static models remain competitive with contextual embeddings, and optimal settings vary across languages and analogical relations. Several key challenges remain, including creating benchmarks that align with human reasoning and understanding what drives differences across methodologies." @default.
- W4385718093 created "2023-08-11" @default.
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- W4385718093 date "2023-01-01" @default.
- W4385718093 modified "2023-09-27" @default.
- W4385718093 title "„Mann“ is to “Donna” as「国王」is to « Reine » Adapting the Analogy Task for Multilingual and Contextual Embeddings" @default.
- W4385718093 doi "https://doi.org/10.18653/v1/2023.starsem-1.25" @default.
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