--- title: "Who cites A Convolutional Attention Network — 72 citing papers" description: "72 papers of the Elamur Research library cite «A Convolutional Attention Network for Extreme Summarization of Source Code», found in their…" canonical: "https://research.elamur.ai/free/en/papers/allamanis-2016-convolutional-attention-network-extreme-summarization/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/allamanis-2016-convolutional-attention-network-extreme-summarization/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [A Convolutional Attention Network for Extreme…](https://md.research.elamur.ai/free/en/papers/allamanis-2016-convolutional-attention-network-extreme-summarization/) / cited by # Who cites «A Convolutional Attention Network for Extreme Summarization of Source Code» 72 papers of our library cite it (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · [← back to «A Convolutional Attention Network for Extreme Summarization of Source Code»](https://md.research.elamur.ai/free/en/papers/allamanis-2016-convolutional-attention-network-extreme-summarization/) 1. [**Program Synthesis with Large Language Models arXiv:2108.07732**Jacob Austin, Augustus Odena, Maxwell Nye, et al.*2021 · 1,192 citations*](https://md.research.elamur.ai/free/en/papers/austin-2021-program-synthesis-large-language-models/) 2. **[Explainable Prediction of Medical Codes from Clinical Text](https://md.research.elamur.ai/free/en/papers/mullenbach-2018-explainable-prediction-medical-codes-clinical/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**James Mullenbach, Sarah Wiegreffe, Jon Duke, et al.*2018 · 720 citations* 3. [**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/) 4. **[Deep Keyphrase Generation](https://md.research.elamur.ai/free/en/papers/meng-2017-deep-keyphrase-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Meng, Sanqiang Zhao, Shuguang Han, et al.*2017 · 454 citations* 5. **[A Transformer-based Approach for Source Code Summarization](https://md.research.elamur.ai/free/en/papers/ahmad-2020-transformer-based-approach-source-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al.*2020 · 431 citations* 6. **[Latent Predictor Networks for Code Generation](https://md.research.elamur.ai/free/en/papers/ling-2016-latent-predictor-networks-code-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wang Ling, Phil Blunsom, Edward Grefenstette, et al.*2016 · 393 citations* 7. [**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/) 8. [**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/) 9. **[Incorporating Discrete Translation Lexicons into Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/arthur-2016-incorporating-discrete-translation-lexicons-into/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Philip Arthur, Graham Neubig, Satoshi Nakamura*2016 · 302 citations* 10. **[Mapping Language to Code in Programmatic Context](https://md.research.elamur.ai/free/en/papers/iyer-2018-mapping-language-code-programmatic-context/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, et al.*2018 · 260 citations* 11. **[Few-Shot and Zero-Shot Multi-Label Learning for Structured Label Spaces](https://md.research.elamur.ai/free/en/papers/rios-2018-few-shot-zero-shot-multi/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Anthony Rios, Ramakanth Kavuluru*2018 · 246 citations* 12. **[Retrieval Augmented Code Generation and Summarization](https://md.research.elamur.ai/free/en/papers/parvez-2021-retrieval-augmented-code-generation-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, et al.*2021 · 193 citations* 13. **[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* 14. **[What makes a convincing argument? Empirical analysis and detecting attributes of convincingness in Web argumentation](https://md.research.elamur.ai/free/en/papers/habernal-2016-what-makes-convincing-argument-empirical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ivan Habernal, Iryna Gurevych*2016 · 165 citations* 15. [**Dialogue Act Recognition via CRF-Attentive Structured Network arXiv:1711.05568**Zheqian Chen, Rongqin Yang, Zhou Zhao, et al.*2017 · 133 citations*](https://md.research.elamur.ai/free/en/papers/chen-2017-dialogue-act-recognition-crf-attentive/) 16. [**Learning to Represent Programs with Graphs arXiv:1711.00740**Miltiadis Allamanis, Marc Brockschmidt, Mahmoud Khademi*2017 · 127 citations*](https://md.research.elamur.ai/free/en/papers/allamanis-2017-learning-represent-programs-graphs/) 17. [**Learning to Prove Theorems via Interacting with Proof Assistants arXiv:1905.09381**Kaiyu Yang, Jia Deng*2019 · 90 citations*](https://md.research.elamur.ai/free/en/papers/yang-2019-learning-prove-theorems-interacting-proof/) 18. **[JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation](https://md.research.elamur.ai/free/en/papers/agashe-2019-juice-large-scale-distantly-supervised/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rajas Agashe, Srinivasan Iyer, Luke Zettlemoyer*2019 · 75 citations* 19. [**code2seq: Generating Sequences from Structured Representations of Code arXiv:1808.01400**Uri Alon, Shaked Brody, Omer Levy, et al.*2018 · 72 citations*](https://md.research.elamur.ai/free/en/papers/alon-2018-code2seq-generating-sequences-structured-representations/) 20. **[Exploring Different Dimensions of Attention for Uncertainty Detection](https://md.research.elamur.ai/free/en/papers/adel-2017-exploring-different-dimensions-attention-uncertainty/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Heike Adel, Hinrich Schütze*2017 · 63 citations* 52 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/allamanis-2016-convolutional-attention-network-extreme-summarization/) — A Convolutional Attention Network for Extreme Summarization of Source Code