Papers with latent-variable model

3 papers
A Discriminative Latent-Variable Model for Bilingual Lexicon Induction (D18-1)

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Challenge: Existing methods for bilingual lexicon induction take advantage of word embeddings, but our model is not as efficient as previous work.
Approach: They propose a discriminative latent-variable model for bilingual lexicon induction that combines the bipartite matching dictionary prior and an embedding-based approach.
Outcome: The proposed model outperforms existing models on six language pairs and shows that it mitigates hubness problem.
Latent Group Dropout for Multilingual and Multidomain Machine Translation (2022.findings-naacl)

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Challenge: Multidomain and multilingual machine translation often rely on parameter sharing strategies, which are hardcoded in the network architecture, independent of the similarities between tasks.
Approach: They propose a method to take advantage of similarities by using a latent-variable model and develop techniques to train this model end-to-end.
Outcome: The proposed model improves translation performance without increasing the model size.
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model (2020.emnlp-main)

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Challenge: Existing models of crosslinguistic adjective ordering have relied on native speakers' intuitive judgment, not corpus data.
Approach: They propose a latent-variable model that can order adjectives across 24 languages . they use tools and techniques to find universal, cross-linguistic, hierarchical ordering tendencies .
Outcome: The proposed model can order adjectives across 24 languages even when languages are different . similar ordering preferences have been found to apply universally across languages .

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