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{"paper_url": "https://huggingface.co/papers/2405.14906", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [InverseCoder: Unleashing the Power of Instruction-Tuned Code LLMs with Inverse-Instruct](https://huggingface.co/papers/2407.05700) (2024)\n* [ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation](https://huggingface.co/papers/2405.17057) (2024)\n* [PLUM: Preference Learning Plus Test Cases Yields Better Code Language Models](https://huggingface.co/papers/2406.06887) (2024)\n* [AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source Data](https://huggingface.co/papers/2405.19265) (2024)\n* [McEval: Massively Multilingual Code Evaluation](https://huggingface.co/papers/2406.07436) (2024)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"}
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