A large-scale study finds that many LLM code translation failures are false negatives due to improper evaluation configurations rather than incorrect translations.
Inter- trans: Leveraging transitive intermediate translations to enhance llm-based code translation
3 Pith papers cite this work. Polarity classification is still indexing.
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A survey of methods, benchmarks, and open challenges for large language models in multilingual code generation and translation.
NL specifications alone do not improve LLM code translation performance, but combining them with source code yields gains in select language pairs with no overall consistent benefit.
citing papers explorer
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Beyond Translation Accuracy: Addressing False Failures in LLM-Based Code Translation
A large-scale study finds that many LLM code translation failures are false negatives due to improper evaluation configurations rather than incorrect translations.
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Large Language Models for Multilingual Code Intelligence: A Survey
A survey of methods, benchmarks, and open challenges for large language models in multilingual code generation and translation.
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Specification-Driven Code Translation Powered by Large Language Models: How Far Are We?
NL specifications alone do not improve LLM code translation performance, but combining them with source code yields gains in select language pairs with no overall consistent benefit.