@inproceedings{sonkin-etal-2026-separating,
title = "Separating Syntax from Language: A Mechanistic Account of Translation in Multilingual {LLM}s",
author = "Sonkin, Mikhail and
Baeumel, Tanja and
Gurgurov, Daniil and
Van Genabith, Josef and
Ostermann, Simon",
editor = "Lee, Hung-Yi and
Dev, Sunipa and
Li, Jessy and
Elliott, Desmond",
booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {EMNLP} 2026",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.findings-emnlp.2115/",
pages = "45092--45112",
ISBN = "979-8-89176-462-0",
abstract = "Multilingual large language models (mLLMs) achieve strong performance in machine translation, yet our understanding of the mechanisms by which they transform representations from one language to another remains incomplete. Prior work suggests that translation decomposes into separable processes within an mLLM, where conceptual content is first represented independently, followed by a production into language-specific form.\par In this work, we show that translation is even more modular than previously assumed and that the output language production in translation processes is actually further separable into a syntax and a surface language process. We construct controlled multilingual datasets that isolate cross-linguistic differences in word order and use causal interventions and probing to track how representations are transformed during translation. We find that models first construct target-side word order before realizing the target language surface form. We identify individual attention heads that are selectively sensitive to syntactic transformations while remaining largely invariant to language identity. These results establish the commitment to a syntactic structure as an independent stage in translation, extending prior decompositions and showing how translation is implemented by functionally different components within mLLMs."
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<abstract>Multilingual large language models (mLLMs) achieve strong performance in machine translation, yet our understanding of the mechanisms by which they transform representations from one language to another remains incomplete. Prior work suggests that translation decomposes into separable processes within an mLLM, where conceptual content is first represented independently, followed by a production into language-specific form.\par In this work, we show that translation is even more modular than previously assumed and that the output language production in translation processes is actually further separable into a syntax and a surface language process. We construct controlled multilingual datasets that isolate cross-linguistic differences in word order and use causal interventions and probing to track how representations are transformed during translation. We find that models first construct target-side word order before realizing the target language surface form. We identify individual attention heads that are selectively sensitive to syntactic transformations while remaining largely invariant to language identity. These results establish the commitment to a syntactic structure as an independent stage in translation, extending prior decompositions and showing how translation is implemented by functionally different components within mLLMs.</abstract>
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%0 Conference Proceedings
%T Separating Syntax from Language: A Mechanistic Account of Translation in Multilingual LLMs
%A Sonkin, Mikhail
%A Baeumel, Tanja
%A Gurgurov, Daniil
%A Van Genabith, Josef
%A Ostermann, Simon
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Findings of the Association for Computational Linguistics: EMNLP 2026
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-462-0
%F sonkin-etal-2026-separating
%X Multilingual large language models (mLLMs) achieve strong performance in machine translation, yet our understanding of the mechanisms by which they transform representations from one language to another remains incomplete. Prior work suggests that translation decomposes into separable processes within an mLLM, where conceptual content is first represented independently, followed by a production into language-specific form.\par In this work, we show that translation is even more modular than previously assumed and that the output language production in translation processes is actually further separable into a syntax and a surface language process. We construct controlled multilingual datasets that isolate cross-linguistic differences in word order and use causal interventions and probing to track how representations are transformed during translation. We find that models first construct target-side word order before realizing the target language surface form. We identify individual attention heads that are selectively sensitive to syntactic transformations while remaining largely invariant to language identity. These results establish the commitment to a syntactic structure as an independent stage in translation, extending prior decompositions and showing how translation is implemented by functionally different components within mLLMs.
%U https://aclanthology.org/2026.findings-emnlp.2115/
%P 45092-45112
Markdown (Informal)
[Separating Syntax from Language: A Mechanistic Account of Translation in Multilingual LLMs](https://aclanthology.org/2026.findings-emnlp.2115/) (Sonkin et al., Findings 2026)
ACL