# Towards Neural Decompilation

> The paper trains a neural machine translation decompiler using a compiler. It evaluates translation from LLVM IR and x86 assembly to C, successfully decompiling over 97% and 88% of its respective benchmarks.

- Authors: Omer Katz; Yuval Olshaker; Yoav Goldberg; Eran Yahav
- Venue: arXiv
- Status: Preprint
- Publication / posting date: May 20, 2019
- Date source: First arXiv submission date.
- First arXiv submission: May 20, 2019
- arXiv: 1905.08325
- Reviewed arXiv version: v1
- Sources reviewed: 2026-11-06
- Added to the catalog: 2026-11-06
- Original paper: <https://arxiv.org/abs/1905.08325>
- PDF: <https://arxiv.org/pdf/1905.08325>
- BibTeX: <https://awesomerea.org/papers/citations/paper-neural-decompilation.bib>
- Catalog page: <https://awesomerea.org/papers/paper-neural-decompilation/>
- Record JSON: <https://awesomerea.org/papers/paper-neural-decompilation/record.json>
- Chinese version: [简体中文](https://awesomerea.org/zh/papers/paper-neural-decompilation/index.md)

## Scope and limitations

The evaluation covers LLVM IR and x86 assembly translated to C on the paper's benchmarks.

## Why it fits this collection

It addresses reverse engineering by recovering human-readable source code from low-level program representations.

## Publication and review notes

The date and venue come from the arXiv record.

## Primary sources

1. <https://arxiv.org/abs/1905.08325>

## About this entry

Reviewed against the paper and its primary sources. Cite the original authors using the linked paper or BibTeX.
Original editorial content: MIT. Linked projects, papers and assets retain their own rights and licenses.