@inproceedings{zhu-etal-2026-latextrans,
title = "{L}a{T}e{XT}rans Structure-Aware Translation of Complex {L}a{T}e{X} Documents",
author = "Zhu, Ziming and
Wang, Chenglong and
Xu, Haosong and
Xing, Shunjie and
Huo, Yifu and
Tian, Fengning and
Du, Quan and
Yang, Di and
Zhang, Chunliang and
Xiao, Tong and
Zhu, JingBo",
editor = "T.Y.S.S., Santosh and
Agarwal, Amit and
Gupta, Vivek and
Kementchedjhieva, Yova and
Garimella, Aparna and
Hou, Yufang",
booktitle = "The Proceedings of Workshop on Document Intelligence and Understanding",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.docinsights-1.23/",
pages = "324--343",
ISBN = "979-8-89176-477-4",
abstract = "Translating LaTeX documents is challenging because natural-language content is tightly interleaved with executable structures such as commands, equations, environments, and cross-references. Direct translation may therefore corrupt document structure and lead to formatting errors or compilation failures. We present LaTeXTrans, a structure-aware framework that separates semantic translation from executable LaTeX structure through four stages: structure-aware parsing, protected translation, structural validation, and document reconstruction. LaTeXTrans isolates non-translatable structures with protected placeholders, validates structural constraints after translation, and reconstructs the translated content into the original multi-file project structure. We evaluate LaTeXTrans on 100 real-world LaTeX projects across multiple domains and translation directions. Experimental results show consistent improvements in translation quality over direct large language model (LLM) translation while maintaining strong structural reliability. On English{--}Chinese translation, LaTeXTrans achieves a 97{\%} compilation success rate with only 0.43 formatting errors per document on average. Controlled experiments further show that its structural performance remains stable when previously unseen user-defined command and environment identifiers are introduced."
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<abstract>Translating LaTeX documents is challenging because natural-language content is tightly interleaved with executable structures such as commands, equations, environments, and cross-references. Direct translation may therefore corrupt document structure and lead to formatting errors or compilation failures. We present LaTeXTrans, a structure-aware framework that separates semantic translation from executable LaTeX structure through four stages: structure-aware parsing, protected translation, structural validation, and document reconstruction. LaTeXTrans isolates non-translatable structures with protected placeholders, validates structural constraints after translation, and reconstructs the translated content into the original multi-file project structure. We evaluate LaTeXTrans on 100 real-world LaTeX projects across multiple domains and translation directions. Experimental results show consistent improvements in translation quality over direct large language model (LLM) translation while maintaining strong structural reliability. On English–Chinese translation, LaTeXTrans achieves a 97% compilation success rate with only 0.43 formatting errors per document on average. Controlled experiments further show that its structural performance remains stable when previously unseen user-defined command and environment identifiers are introduced.</abstract>
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%0 Conference Proceedings
%T LaTeXTrans Structure-Aware Translation of Complex LaTeX Documents
%A Zhu, Ziming
%A Wang, Chenglong
%A Xu, Haosong
%A Xing, Shunjie
%A Huo, Yifu
%A Tian, Fengning
%A Du, Quan
%A Yang, Di
%A Zhang, Chunliang
%A Xiao, Tong
%A Zhu, JingBo
%Y T.Y.S.S., Santosh
%Y Agarwal, Amit
%Y Gupta, Vivek
%Y Kementchedjhieva, Yova
%Y Garimella, Aparna
%Y Hou, Yufang
%S The Proceedings of Workshop on Document Intelligence and Understanding
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-477-4
%F zhu-etal-2026-latextrans
%X Translating LaTeX documents is challenging because natural-language content is tightly interleaved with executable structures such as commands, equations, environments, and cross-references. Direct translation may therefore corrupt document structure and lead to formatting errors or compilation failures. We present LaTeXTrans, a structure-aware framework that separates semantic translation from executable LaTeX structure through four stages: structure-aware parsing, protected translation, structural validation, and document reconstruction. LaTeXTrans isolates non-translatable structures with protected placeholders, validates structural constraints after translation, and reconstructs the translated content into the original multi-file project structure. We evaluate LaTeXTrans on 100 real-world LaTeX projects across multiple domains and translation directions. Experimental results show consistent improvements in translation quality over direct large language model (LLM) translation while maintaining strong structural reliability. On English–Chinese translation, LaTeXTrans achieves a 97% compilation success rate with only 0.43 formatting errors per document on average. Controlled experiments further show that its structural performance remains stable when previously unseen user-defined command and environment identifiers are introduced.
%U https://aclanthology.org/2026.docinsights-1.23/
%P 324-343
Markdown (Informal)
[LaTeXTrans Structure-Aware Translation of Complex LaTeX Documents](https://aclanthology.org/2026.docinsights-1.23/) (Zhu et al., DocInsights 2026)
ACL
- Ziming Zhu, Chenglong Wang, Haosong Xu, Shunjie Xing, Yifu Huo, Fengning Tian, Quan Du, Di Yang, Chunliang Zhang, Tong Xiao, and JingBo Zhu. 2026. LaTeXTrans Structure-Aware Translation of Complex LaTeX Documents. In The Proceedings of Workshop on Document Intelligence and Understanding, pages 324–343, Budapest, Hungary. Association for Computational Linguistics.