Sign inGet started
Paper · arXiv

Hallucinations of Large Language Models in Cross-Language Code Translation: Phenomena and Mitigation

Code translation converts source code from one programming language to another while preserving its functionality. Although Large Language Models (LLMs) have improved code translation, their outputs still contain hallucinations: generated code that conflicts with the source program, violates target-language facts, or introduces contextually inconsistent dependencies. These failures are especially harmful in translation because small semantic deviations can silently change program behavior. Existing hallucination studies mainly focus on natural-language generation or code generation, leaving the forms, distribution, and mitigation of hallucinations in cross-language code translation insuff...

AuthorsYali Du, Yunji Zhang, Ming Li
Primary categorycs.SE
Published20 October 2026
Last updated at source20 October 2026
cs.SEcs.AI
Embed this entry
<iframe src="https://silytics.si/embed/item/dd985787-1414-4cb4-8f0e-6d83c75767f8" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 21 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.