--- title: "Who cites A parallel corpus of Python — 39 citing papers" description: "39 papers of the Elamur Research library cite «A parallel corpus of Python functions and documentation strings for automated code…" canonical: "https://research.elamur.ai/free/en/papers/barone-2017-parallel-corpus-python-functions-documentation/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/barone-2017-parallel-corpus-python-functions-documentation/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [A parallel corpus of Python functions and…](https://md.research.elamur.ai/free/en/papers/barone-2017-parallel-corpus-python-functions-documentation/) / cited by # Who cites «A parallel corpus of Python functions and documentation strings for automated code documentation and code generation» 39 papers of our library cite it (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← back to «A parallel corpus of Python functions and documentation strings for automated code documentation and code generation»](https://md.research.elamur.ai/free/en/papers/barone-2017-parallel-corpus-python-functions-documentation/) 1. [**Evaluating Large Language Models Trained on Code arXiv:2107.03374**Mark Chen, Jerry Tworek, Heewoo Jun, et al.*2021 · 2,659 citations*](https://md.research.elamur.ai/free/en/papers/chen-2021-evaluating-large-language-models-trained/) 2. [**CodeSearchNet Challenge: Evaluating the State of Semantic Code Search arXiv:1909.09436**Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, et al.*2020 · 656 citations*](https://md.research.elamur.ai/free/en/papers/husain-2020-codesearchnet-challenge-evaluating-state-semantic/) 3. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/) 4. [**The Adverse Effects of Code Duplication in Machine Learning Models of Code arXiv:1812.06469**Miltiadis Allamanis*2018 · 319 citations*](https://md.research.elamur.ai/free/en/papers/allamanis-2018-adverse-effects-code-duplication-machine/) 5. [**Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow arXiv:1805.08949**Pengcheng Yin, Bowen Deng, Edgar Chen, et al.*2018 · 308 citations*](https://md.research.elamur.ai/free/en/papers/yin-2018-learning-mine-aligned-code-natural/) 6. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/) 7. **[A Survey of Machine Learning for Big Code and Naturalness](https://md.research.elamur.ai/free/en/papers/allamanis-2017-survey-machine-learning-big-code/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, et al.*2017 · 167 citations* 8. [**Unsupervised Translation of Programming Languages arXiv:2006.03511**Marie-Anne Lachaux, Baptiste Roziere, Lowik Chanussot, et al.*2020 · 160 citations*](https://md.research.elamur.ai/free/en/papers/lachaux-2020-unsupervised-translation-programming-languages/) 9. **[PyMT5: multi-mode translation of natural language and Python code with transformers](https://md.research.elamur.ai/free/en/papers/clement-2020-pymt5-multi-mode-translation-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Colin Clement, Dawn Drain, Jonathan Timcheck, et al.*2020 · 158 citations* 10. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/) 11. **[Natural Language to Code Translation with Execution](https://md.research.elamur.ai/free/en/papers/shi-2022-natural-language-code-translation-execution/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Freda Shi, Daniel Fried, Marjan Ghazvininejad, et al.*2022 · 116 citations* 12. **[XCodeEval: An Execution-based Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval](https://md.research.elamur.ai/free/en/papers/khan-2024-xcodeeval-execution-based-large-scale/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2024 · 51 citations* 13. [**xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval arXiv:2303.03004**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/khan-2023-xcodeeval-large-scale-multilingual-multitask/) 14. [**Leveraging Automated Unit Tests for Unsupervised Code Translation arXiv:2110.06773**Baptiste Roziere, Jie M. Zhang, Francois Charton, et al.*2022 · 40 citations*](https://md.research.elamur.ai/free/en/papers/roziere-2022-leveraging-automated-unit-tests-unsupervised/) 15. **[Fault-Aware Neural Code Rankers](https://md.research.elamur.ai/free/en/papers/inala-2022-fault-aware-neural-code-rankers/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jeevana Priya Inala, Chenglong Wang, Mei Yang, et al.*2022 · 39 citations* 24 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/barone-2017-parallel-corpus-python-functions-documentation/) — A parallel corpus of Python functions and documentation strings for automated code documentation and code generation