<p>I suggest you take a look at the syllabus of <a href="http://cs224d.stanford.edu/syllabus.html" rel="nofollow noreferrer">http://cs224d.stanford.edu/syllabus.html</a> and see what was invented in the last ~20 years. They focus on deep learning methods, and they include there almost everything important.</p>

<p>Among the things, which I would include into the review are:</p>

<ul>
<li>Word2Vec models</li>
<li>Seq2Seq models</li>
</ul>

<p>Concerning what happened in the last 5 years, i.e. since 2013, I suggest you mentioning super human performance on the SQuAD 1.1 dataset: <a href="https://rajpurkar.github.io/SQuAD-explorer/" rel="nofollow noreferrer">https://rajpurkar.github.io/SQuAD-explorer/</a> </p>

CC BY-SA 4.0
2020-12-21T00:51:52.023Z
It may be worth editing this answer to mention the transformers and related models.
nbro
CC BY-SA 4.0
2018-12-21T02:52:29.447Z
2018-12-21T03:03:12.427Z
2018-12-21T03:03:12.427Z
Konstantin Solomatov
<p>I'm looking at the history of NLP, starting in the 1950s, with the <a href="http://www.hutchinsweb.me.uk/AMTA-2004.pdf" rel="nofollow noreferrer">Georgetown–IBM experiment</a>.</p>

<p>What are examples of the most recent (e.g. in the last 5-10 years) and influential breakthroughs in natural language processing?</p>

<machine-learning><natural-language-processing><research><history><natural-language-understanding>
What are the most recent and influential breakthroughs in NLP?
csheroe
# What are the most recent and influential breakthroughs in NLP?

(Asked by: username_0 on 2017-04-05)

I'm looking at the history of NLP, starting in the 1950s, with the [Georgetown–IBM experiment](http://www.hutchinsweb.me.uk/AMTA-2004.pdf).

What are examples of the most recent (e.g. in the last 5-10 years) and influential breakthroughs in natural language processing?

**Tags:** machine-learning, natural-language-processing, research, history, natural-language-understanding


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## 1 answers

### Answer by username_1 on 2018-12-21. Score: 2

I suggest you take a look at the syllabus of <http://cs224d.stanford.edu/syllabus.html> and see what was invented in the last ~20 years. They focus on deep learning methods, and they include there almost everything important.

Among the things, which I would include into the review are:

* Word2Vec models
* Seq2Seq models

Concerning what happened in the last 5 years, i.e. since 2013, I suggest you mentioning super human performance on the SQuAD 1.1 dataset: <https://rajpurkar.github.io/SQuAD-explorer/>

> **Comments:**
> **username_2**: It may be worth editing this answer to mention the transformers and related models.  

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