# kTrans: Knowledge-Aware Transformer for Binary Code Embedding

> kTrans uses a knowledge-aware Transformer to embed binary code. It evaluates the embeddings through outlier detection and visualization, and on binary code similarity, function type recovery, and indirect call recognition.

- Authors: Wenyu Zhu; Hao Wang; Yuchen Zhou; Jiaming Wang; Zihan Sha; Zeyu Gao; Chao Zhang
- Venue: arXiv
- Status: Preprint
- Publication / posting date: August 24, 2023
- Date source: First arXiv submission date.
- First arXiv submission: August 24, 2023
- arXiv: 2308.12659
- Reviewed arXiv version: v1
- Sources reviewed: 2026-11-06
- Added to the catalog: 2026-11-06
- Original paper: <https://arxiv.org/abs/2308.12659>
- PDF: <https://arxiv.org/pdf/2308.12659>
- Code: <https://github.com/Learner0x5a/kTrans-release>
- BibTeX: <https://awesomerea.org/papers/citations/paper-ktrans.bib>
- Catalog page: <https://awesomerea.org/papers/paper-ktrans/>
- Record JSON: <https://awesomerea.org/papers/paper-ktrans/record.json>
- Chinese version: [简体中文](https://awesomerea.org/zh/papers/paper-ktrans/index.md)

## Scope and limitations

Covers binary code and three downstream tasks: binary code similarity detection, function type recovery and indirect call recognition, with reported improvements of 5.2%, 6.8% and 12.6%.

## Why it fits this collection

It applies binary code embeddings to reverse-engineering tasks.

## Publication and review notes

The date and venue come from the arXiv record.

## Primary sources

1. <https://arxiv.org/abs/2308.12659>

## 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.