Papers with cross-lingual mapping

2 papers
IsoVec: Controlling the Relative Isomorphism of Word Embedding Spaces (2022.emnlp-main)

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Challenge: a faulty cross-lingual mapping technique results in non-isomorphic word embedding spaces . we address the root-cause of this problem by increasing the relative isomorphism of word embedsing spaces.
Approach: They address the root-cause of faulty cross-lingual mapping by incorporating global measures of isomorphism into the skipgram loss function.
Outcome: The proposed method improves bilingual lexicon induction under domain mismatch and with training algorithm dissimilarities.
Improving Multilingual Neural Machine Translation by Utilizing Semantic and Linguistic Features (2024.findings-acl)

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Challenge: Existing models do not differentiate between semantic and linguistic features, resulting in the entanglement of knowledge and linguistics within the model.
Approach: They propose to exploit both semantic and linguistic features to enhance multilingual translation by disentangling encoder representations and integrating low-level linguistic encoders.
Outcome: The proposed model improves zero-shot translation while maintaining performance in supervised translation on multilingual datasets.

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