Related papers: Large Language Models for Multilingual Code Intelligence: A Survey

Large Language Models for Multilingual Code Intelligence: A Survey

URL: http://arxiv.org/abs/2604.25960v1
Date: Mon, 27 Apr 2026 20:20:26 GMT
Title: Large Language Models for Multilingual Code Intelligence: A Survey
Abstract summary: This survey focuses on two key tasks: multilingual code generation from shared natural-language requirements, and multilingual code translation that preserves semantics across languages.<n>It reviews representative methods, benchmarks, and evaluation metrics, and highlights challenges and opportunities for trustworthy cross-language generalization.
Score: 15.859504186659825
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Large language models have transformed AI-assisted software engineering, but current research remains biased toward high-resource languages such as Python, with weaker performance in languages like Rust and OCaml. Since real-world systems are inherently polyglot, robust multilingual code intelligence is crucial. This survey focuses on two key tasks: multilingual code generation from shared natural-language requirements, and multilingual code translation that preserves semantics across languages. It reviews representative methods, benchmarks, and evaluation metrics, and highlights challenges and opportunities for trustworthy cross-language generalization.

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