An Analysis of Euclidean vs. Graph-Based Framing for Bilingual Lexicon Induction from Word Embedding Spaces (2021.findings-emnlp)
Copied to clipboard
Kelly Marchisio, Youngser Park, Ali Saad-Eldin, Anton Alyakin, Kevin Duh, Carey Priebe, Philipp Koehn
| Challenge: | Existing work in bilingual lexicon induction views word embeddings as vectors in Euclidean space. |
| Approach: | They propose to use word embeddings as nodes in a weighted graph to examine a node’s graph neighborhood without assuming a linear transform. |
| Outcome: | The proposed approaches are compared under different data conditions and show that they complement each other when combined. |
Similar Papers
Combining Static Word Embeddings and Contextual Representations for Bilingual Lexicon Induction (2021.findings-acl)
Copied to clipboard
| 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. |
LNMap: Departures from Isomorphic Assumption in Bilingual Lexicon Induction Through Non-Linear Mapping in Latent Space (2020.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods for bilingual lexicon induction are mapping-based, but they do not hold for closely related languages. |
| Approach: | They propose a semi-supervised method to learn cross-lingual word embeddings for BLI using a linear mapping function and a latent space of two independently trained autoencoders. |
| Outcome: | The proposed method outperforms existing models on 15 different language pairs on both directions. |
A Graph-based Coarse-to-fine Method for Unsupervised Bilingual Lexicon Induction (2020.acl-main)
Copied to clipboard
| Challenge: | Recent methods for bilingual lexicon induction are based on unsupervised cross-lingual word embeddings . previous methods only use word-level information, which is limited and inaccurate . |
| Approach: | They propose a graph-based approach to induce bilingual lexicons in a coarse-to-fine way . they use word cliques from graphs and aligned clique-level words to find initial translation solution . |
| Outcome: | The proposed method improves the performance of bilingual lexicon induction compared with previous methods. |
A Structure-Aware Generative Adversarial Network for Bilingual Lexicon Induction (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Bilingual lexicon induction (BLI) is the task of inducing word translations with a learned mapping function that aligns monolingual word embedding spaces in two different languages. |
| Approach: | They propose a model that explicitly captures multiple topological structure information to achieve accurate bilingual lexicon induction. |
| Outcome: | The proposed model captures multiple topological structure information to achieve accurate BLI on a public dataset. |
How Lexical is Bilingual Lexicon Induction? (2024.findings-naacl)
Copied to clipboard
| Challenge: | lexical variation and low-resource settings make it difficult to learn in low-level settings. |
| Approach: | They propose to incorporate additional lexical information into the retrieve-and-rank approach to improve lexicon induction. |
| Outcome: | The proposed approach improves on XLING by an average of 2% across all language pairs. |
Orthographic Features for Bilingual Lexicon Induction (P18-2)
Copied to clipboard
| Challenge: | Recent embedding-based methods do not take advantage of orthographic features, such as edit distance, which can be helpful for pairs of related languages. |
| Approach: | They propose to use orthographic features to integrate orthographic induction into embedding methods . they use document-aligned data instead of a seed dictionary to learn bilingual embedds . |
| Outcome: | This work extends embedding-based methods to incorporate orthographic features . it shows that the methods can learn bilingual embeddables in low-resource languages . |
DM-BLI: Dynamic Multiple Subspaces Alignment for Unsupervised Bilingual Lexicon Induction (2024.acl-long)
Copied to clipboard
| Challenge: | Existing approaches to unsupervised bilingual lexicon induction (BLI) fail on distant or low-resource language pairs, achieving less than half the performance observed in rich-resourced languages. |
| Approach: | They propose a framework for unsupervised bilingual lexicon induction that uses multiple subspace alignments instead of a single mapping. |
| Outcome: | Experiments on 12 language pairs show that the proposed framework improves language alignment by utilizing multiple subspace alignments instead of a single mapping. |
When Your Cousin Has the Right Connections: Unsupervised Bilingual Lexicon Induction for Related Data-Imbalanced Languages (2024.lrec-main)
Copied to clipboard
| Challenge: | Existing methods for unsupervised bilingual lexicon induction depend on good quality static or contextual embeddings for both languages. |
| Approach: | They propose a method for unsupervised bilingual lexicon induction between a related LRL and a high-resource language that only requires inference on a masked language model of the HRL. |
| Outcome: | The proposed method performs well on low-resource languages with 5M tokens against Hindi . it is compared with existing methods on (mid-resourced) Marathi and Nepali . |
Bilingual Lexicon Induction with Semi-supervision in Non-Isometric Embedding Spaces (P19-1)
Copied to clipboard
| Challenge: | Recent work on bilingual lexicon induction (BLI) relies on an assumption about the isometry of two embedding spaces. |
| Approach: | They propose a semi-supervised approach that relaxes the isometric assumption while leveraging limited aligned bilingual lexicons and a larger set of unaligned word embeddings. |
| Outcome: | The proposed method obtains state-of-the-art results on 15 of 18 language pairs on the MUSE dataset and does particularly well when the embedding spaces don’t appear isometric. |
Combining Word Embeddings with Bilingual Orthography Embeddings for Bilingual Dictionary Induction (2020.coling-main)
Copied to clipboard
| Challenge: | Bilingual dictionary induction (BDI) is a task of finding target language translations of source language words. |
| Approach: | They propose to use bilingual orthography Embeddings to enrich BWE-based BDI with transliteration information to make a decision on which information source is more reliable for a particular word pair. |
| Outcome: | The proposed system improves on English-Russian BDI and shows that it can be built with only weak bilingual signals and even without any bilingual signal. |