Papers by Nini Xiao

2 papers
Combining Static Word Embeddings and Contextual Representations for Bilingual Lexicon Induction (2021.findings-acl)

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Challenge: Bilingual Lexicon Induction (BLI) aims to map words in one language to their translations in another.
Approach: They propose a mechanism to combine static word embeddings and contextual representations to utilize the advantages of both paradigms.
Outcome: The proposed method improves performance on supervised and unsupervised BLI benchmarks on all language pairs by average improving 3.2 points over baselines.
Disambiguated Lexically Constrained Neural Machine Translation (2023.findings-acl)

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Challenge: Current approaches to LCNMT assume that pre-specified lexicon constraints are contextually appropriate.
Approach: They propose a framework that disambiguates constraints based on contexts at first and integrates them into LCNMT.
Outcome: The proposed approach outperforms baseline approaches on benchmark datasets and comprehensive experiments in multiple target constraints.

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