Cross-Lingual Word Embeddings
32 papers with code • 0 benchmarks • 0 datasets
Benchmarks
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Libraries
Use these libraries to find Cross-Lingual Word Embeddings models and implementationsMost implemented papers
Word Translation Without Parallel Data
facebookresearch/MUSE
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ICLR 2018
We finally describe experiments on the English-Esperanto low-resource language pair, on which there only exists a limited amount of parallel data, to show the potential impact of our method in fully unsupervised machine translation.
A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings
Recent work has managed to learn cross-lingual word embeddings without parallel data by mapping monolingual embeddings to a shared space through adversarial training.
Lost in Evaluation: Misleading Benchmarks for Bilingual Dictionary Induction
We study the composition and quality of the test sets for five diverse languages from this dataset, with concerning findings: (1) a quarter of the data consists of proper nouns, which can be hardly indicative of BDI performance, and (2) there are pervasive gaps in the gold-standard targets.
A Pilot Study for Chinese SQL Semantic Parsing
The task of semantic parsing is highly useful for dialogue and question answering systems.
Robust Cross-lingual Embeddings from Parallel Sentences
Recent advances in cross-lingual word embeddings have primarily relied on mapping-based methods, which project pretrained word embeddings from different languages into a shared space through a linear transformation.
Transferring Knowledge Distillation for Multilingual Social Event Detection
RingBDStack/CLKD
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Experiments on both synthetic and real-world datasets show the framework to be highly effective at detection in both multilingual data and in languages where training samples are scarce.
Baselines and test data for cross-lingual inference
In this paper, we propose to advance the research in SNLI-style natural language inference toward multilingual evaluation.
Model Transfer for Tagging Low-resource Languages using a Bilingual Dictionary
Cross-lingual model transfer is a compelling and popular method for predicting annotations in a low-resource language, whereby parallel corpora provide a bridge to a high-resource language and its associated annotated corpora.
Improving Cross-Lingual Word Embeddings by Meeting in the Middle
Cross-lingual word embeddings are becoming increasingly important in multilingual NLP.
How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some Misconceptions
In this work, we make the first step towards a comprehensive evaluation of cross-lingual word embeddings.
