Bilingual Lexicon Induction
34 papers with code • 0 benchmarks • 0 datasets
Translate words from one language to another.
Benchmarks
These leaderboards are used to track progress in Bilingual Lexicon Induction
Latest papers
Semi-Supervised Learning for Bilingual Lexicon Induction
gguinet/semisupervised-alignment
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It was recently shown that it is possible to infer such lexicon, without using any parallel data, by aligning word embeddings trained on monolingual data.
ProMap: Effective Bilingual Lexicon Induction via Language Model Prompting
We also demonstrate the effectiveness of ProMap in re-ranking results from other BLI methods such as with aligned static word embeddings.
On Bilingual Lexicon Induction with Large Language Models
Bilingual Lexicon Induction (BLI) is a core task in multilingual NLP that still, to a large extent, relies on calculating cross-lingual word representations.
When your Cousin has the Right Connections: Unsupervised Bilingual Lexicon Induction for Related Data-Imbalanced Languages
Most existing approaches for unsupervised bilingual lexicon induction (BLI) depend on good quality static or contextual embeddings requiring large monolingual corpora for both languages.
Low-resource Bilingual Dialect Lexicon Induction with Large Language Models
Bilingual word lexicons are crucial tools for multilingual natural language understanding and machine translation tasks, as they facilitate the mapping of words in one language to their synonyms in another language.
Improving Bilingual Lexicon Induction with Cross-Encoder Reranking
This crucial step is done via 1) creating a word similarity dataset, comprising positive word pairs (i. e., true translations) and hard negative pairs induced from the original CLWE space, and then 2) fine-tuning an mPLM (e. g., mBERT or XLM-R) in a cross-encoder manner to predict the similarity scores.
RAPO: An Adaptive Ranking Paradigm for Bilingual Lexicon Induction
jlfj345wf/rapo
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Bilingual lexicon induction induces the word translations by aligning independently trained word embeddings in two languages.
IsoVec: Controlling the Relative Isomorphism of Word Embedding Spaces
The ability to extract high-quality translation dictionaries from monolingual word embedding spaces depends critically on the geometric similarity of the spaces -- their degree of "isomorphism."
Improving Word Translation via Two-Stage Contrastive Learning
cambridgeltl/contrastivebli
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ACL 2022
At Stage C1, we propose to refine standard cross-lingual linear maps between static word embeddings (WEs) via a contrastive learning objective; we also show how to integrate it into the self-learning procedure for even more refined cross-lingual maps.
Improving Word Translation via Two-Stage Contrastive Learning
cambridgeltl/contrastivebli
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ACL ARR November 2021
As Stage C1, we propose to refine standard cross-lingual linear maps between static word embeddings (WEs) via a contrastive learning objective; we also show how to integrate it into the self-learning procedure for even more refined cross-lingual maps.
