<p>The blog post <a href="https://ruder.io/unsupervised-cross-lingual-learning/" rel="nofollow noreferrer">Unsupervised Cross-lingual Representation Learning</a> (2019), the related <a href="https://www.aclweb.org/anthology/P19-4007.pdf" rel="nofollow noreferrer">paper</a> and <a href="https://docs.google.com/presentation/d/1miPu0hkBFSRTAxP-Psg0xXOvAbVSJPhQXehMQdUI88I/edit#slide=id.g5cacfdb6b8_1_137" rel="nofollow noreferrer">slides</a> by Sebastian Ruder (a researcher currently at DeepMind) summarize what you are looking for. In fact, the authors write</p>

<blockquote>
  <p>We will introduce researchers to <strong>state-of-the-art</strong> methods for constructing resource-light cross-lingual word representations and discuss their applicability in a broad range of downstream NLP applications, covering bilingual lexicon induction, machine translation (both neural and phrase-based), dialogue, and information retrieval tasks. We will deliver a detailed survey of the <strong>current cutting-edge methods</strong>, discuss best training and evaluation practices and usecases, and provide links to publicly available implementations, datasets, and pretrained models and word embedding collections.</p>
</blockquote>

CC BY-SA 4.0
2020-03-16T23:07:20.937Z
Maybe later I will update this answer with a list of the SOTA methods/approaches.
nbro
CC BY-SA 4.0
2020-03-16T22:35:27.053Z
2020-03-16T22:35:27.053Z
nbro
<p>What is the current state-of-the-art in unsupervised cross-lingual representation learning?</p>

<natural-language-processing><reference-request><models><state-of-the-art>
What is the current state-of-the-art in unsupervised cross-lingual representation learning?
DRV
# What is the current state-of-the-art in unsupervised cross-lingual representation learning?

(Asked by: username_0 on 2020-03-13)

What is the current state-of-the-art in unsupervised cross-lingual representation learning?

**Tags:** natural-language-processing, reference-request, models, state-of-the-art


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## 1 answers

### Answer by username_1 on 2020-03-16. Score: 1 | Accepted answer

The blog post [Unsupervised Cross-lingual Representation Learning](https://ruder.io/unsupervised-cross-lingual-learning/) (2019), the related [paper](https://www.aclweb.org/anthology/P19-4007.pdf) and [slides](https://docs.google.com/presentation/d/1miPu0hkBFSRTAxP-Psg0xXOvAbVSJPhQXehMQdUI88I/edit#slide=id.g5cacfdb6b8_1_137) by Sebastian Ruder (a researcher currently at DeepMind) summarize what you are looking for. In fact, the authors write

> We will introduce researchers to **state-of-the-art** methods for constructing resource-light cross-lingual word representations and discuss their applicability in a broad range of downstream NLP applications, covering bilingual lexicon induction, machine translation (both neural and phrase-based), dialogue, and information retrieval tasks. We will deliver a detailed survey of the **current cutting-edge methods**, discuss best training and evaluation practices and usecases, and provide links to publicly available implementations, datasets, and pretrained models and word embedding collections.

> **Comments:**
> **username_1**: Maybe later I will update this answer with a list of the SOTA methods/approaches.  

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