Papers with cross-lingual text representation models
AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples (2021.emnlp-main)
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| Challenge: | Existing multilingual evaluation datasets that evaluate lexical semantics "in-context" have various limitations, including limited coverage of high-resource languages and superficial cues. |
| Approach: | They propose to use a set of pretrained language models to evaluate lexical semantics in context. |
| Outcome: | The proposed set shows that current models lag behind human performance in interpreting word meaning in cross-lingual contexts. |