# Ethan Fetaya 2020: Restoration of fragmentary Babylonian texts using recurrent neural networks

> Ethan Fetaya, Yonatan Lifshitz, Elad Aaron et al., 2020. 4 records on Mysteries Department cite it. PNAS 117(37). Recurrent neural network language…

Source: https://mysteriesdept.com/sources/SRC0DEDGV4PQG6J/restoration-of-fragmentary-babylonian-texts-using-recurrent  
Publisher: Mysteries Department  
Licence: CC BY 4.0 (credit Mysteries Department and link the page)  

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[Sources](https://mysteriesdept.com/sources)[Unread cuneiform: half a million tablets and the limits of Sumerian](https://mysteriesdept.com/mysteries/unread-cuneiform)Ethan Fetaya 2020

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# Restoration of fragmentary Babylonian texts using recurrent neural networks

Ethan Fetaya, Yonatan Lifshitz, Elad Aaron et al., 2020.

**Unread cuneiform: half a million tablets and the limits of Sumerian** Articledoi: **[10.1073/pnas.2003794117](https://doi.org/10.1073/pnas.2003794117)** 0

## What it's used for here

PNAS 117(37). Recurrent neural network language models of Achaemenid-period Babylonian (Akkadian) archival texts, used to propose fillings for broken passages; first machine-learning restoration work on cuneiform. Used for the fragment-restoration line of work.

## Cited by on this site 4 records

[Both restoration studies (recurrent networks 2020, masked language models 2021) present their output as suggestions…](https://mysteriesdept.com/mysteries/unread-cuneiform/evidence/EVD0DEDY3FKDT9Y/both-restoration-studies-recurrent-networks-2020-masked)

Evidence

EVD

[Fetaya, Lifshitz, Aaron and Gordin publish recurrent-network restoration of broken Babylonian texts](https://mysteriesdept.com/mysteries/unread-cuneiform/events/EVT0DEDPGKBNTQA/fetaya-lifshitz-aaron-and-gordin-publish-recurrent-network)

EVT

[Shai Gordin](https://mysteriesdept.com/mysteries/unread-cuneiform/people/FIG0DEDNF24S7H7/shai-gordin)

FIG

[The unread cuneiform: half a million tablets and the limits of Sumerian](https://mysteriesdept.com/mysteries/unread-cuneiform)

The mystery article

MYS

## Cite it

```
Ethan Fetaya, Yonatan Lifshitz, Elad Aaron, & Shai Gordin (2020). Restoration of fragmentary Babylonian texts using recurrent neural networks. https://doi.org/10.1073/pnas.2003794117
```

[Find it at doi.org](https://doi.org/10.1073/pnas.2003794117)

Key

**SRC** 0DEDGV4PQG6J

Kind

Journal article

Rights

The publisher's

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The record

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