What does this research mean for the field?

Syntactic complexity in both source texts and GPT-4 generated translations predicts post-editing errors, though expert translators are less negatively impacted by rising complexity than students, particularly during light post-editing. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The aim is to explore how syntactic complexity affects the quality of post-editing in translations from GPT-4.

April 10, 2026Translation Cognition & Behavior0 citationsOpen Access

Dependency-Based Syntactic Complexity and Post-Editing of GPT-4 Translations

How dependency-based syntactic complexity shapes post-editing of LLM-generated translations

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Authors

LZLonghui Zou MCMichaël Carl JFJia Feng

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Overview

Examines the role of syntactic complexity in post-editing outcomes for English-to-Chinese translations, indicating that expertise moderates these effects.

Key Points

The aim is to explore how syntactic complexity affects the quality of post-editing in translations from GPT-4.
Data collected from 46 participants, including students and professionals.
Participants post-edited translations in Trados Studio.
Syntactic complexity operationalized using dependency-based metrics and English–Chinese specific indices.
Complexity in source texts and GPT-4 outputs predicts post-editing errors.
Experts demonstrate lower sensitivity to increasing complexity compared to students.
Termbase access decreases overall and terminology errors; advantage of experts is more pronounced in Light post-editing conditions.

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Cite This Study

Zou et al. (2026) studied this question.

synapsesocial.com/papers/69d895ea6c1944d70ce07068 https://doi.org/10.1075/tcb.00100.zou

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April 10, 2026Translation Cognition & Behavior0 citationsOpen Access

Dependency-Based Syntactic Complexity and Post-Editing of GPT-4 Translations

How dependency-based syntactic complexity shapes post-editing of LLM-generated translations

View Full Paper

Authors

LZLonghui Zou MCMichaël Carl JFJia Feng

Discussion

Member takes

Overview

Examines the role of syntactic complexity in post-editing outcomes for English-to-Chinese translations, indicating that expertise moderates these effects.

Key Points

The aim is to explore how syntactic complexity affects the quality of post-editing in translations from GPT-4.
Data collected from 46 participants, including students and professionals.
Participants post-edited translations in Trados Studio.
Syntactic complexity operationalized using dependency-based metrics and English–Chinese specific indices.
Complexity in source texts and GPT-4 outputs predicts post-editing errors.
Experts demonstrate lower sensitivity to increasing complexity compared to students.
Termbase access decreases overall and terminology errors; advantage of experts is more pronounced in Light post-editing conditions.

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Helpful

Bookmark

View Full Paper

Cite This Study

Zou et al. (2026) studied this question.

synapsesocial.com/papers/69d895ea6c1944d70ce07068 https://doi.org/10.1075/tcb.00100.zou

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