Yali Du, Yunji Zhang, Ming Li · 2026 · arXiv
DOI: 10.48550/arXiv.2610.27868 · open-access PDF
Terjemahan kode mengkonversi kode sumber dari satu bahasa pemrograman ke bahasa lain sambil mempertahankan fungsinya. Meskipun Model Bahasa Besar (LLM) telah meningkatkan terjemahan kode, output mereka masih mengandung halusinasi: kode yang dihasilkan yang bertentangan dengan program sumber, melanggar fakta-fakta bahasa sasaran, atau memperkenalkan ketergantungan yang tidak konsisten secara kontekstual. Kegagalan ini terutama berbahaya dalam terjemahan karena penyimpangan semantik kecil dapat secara diam-diam mengubah perilaku program.
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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