Recommended introductory papers:

1. ExeCoder: Empowering Large Language Models with Executability Representation for Code Translation — Work from Microsoft, proposing some fairly creative ideas.
2. Repository-Level Compositional Code Translation and Validation — File-level approach (the longer the code, the harder the task).
3. CoTran: An LLM-based Code Translator using Reinforcement Learning with Feedback from Compiler and Symbolic Execution — A common method combining compiler feedback and RL, with a well-designed architecture.
4. Lost in Translation: A Study of Bugs Introduced by Large Language Models while Translating Code — A survey-like paper that helps you get up to speed quickly.
5. A Systematic Literature Review on Neural Code Translation — A comprehensive literature review; after reading it, you'll feel like you have a handle on everything.
6. IMPROVING COMPLEX REASONING WITH DYNAMIC PROMPT CORRUPTION: A SOFT PROMPT OPTIMIZATION APPROACH — A paper on prompt engineering; reading it may help you write better prompts.
7. Enhancing LLM-based Code Translation in Repository Context via Triple Knowledge-Augmented — Combines knowledge augmentation with code translation from an interesting angle, and also handles file-level processing.

Feel free to share any great papers you find with everyone!

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• Mira190贡献 2 次 · 最近 2025/09/19
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