Yali Du, Yunji Zhang, Ming Li · 2026 · arXiv
DOI: 10.48550/arXiv.2610.27868 · open-access PDF
Obwohl große Sprachmodelle (LLMs) die Übersetzung von Code verbessert haben, enthalten ihre Ausgaben immer noch Halluzinationen: erzeugter Code, der mit dem Quellprogramm kollidiert, Zielsprachenfakte verletzt oder kontextuell inkonsistente Abhängigkeiten einführt. Diese Fehler sind besonders schädlich bei der Übersetzung, weil kleine semantische Abweichungen das Programmverhalten still ändern können.
Machine translation (Meta M2M100); the English original follows.
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 th
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