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...
| Authors | Yali Du, Yunji Zhang, Ming Li |
|---|---|
| Primary category | cs.SE |
| Published | 20 October 2026 |
| Last updated at source | 20 October 2026 |
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