--- title: "Who cites Latent Predictor Networks for Code Generation" description: "104 papers of the Elamur Research library cite «Latent Predictor Networks for Code Generation», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/ling-2016-latent-predictor-networks-code-generation/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/ling-2016-latent-predictor-networks-code-generation/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Latent Predictor Networks for Code Generation](https://md.research.elamur.ai/free/en/papers/ling-2016-latent-predictor-networks-code-generation/) / cited by # Who cites «Latent Predictor Networks for Code Generation» 104 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← back to «Latent Predictor Networks for Code Generation»](https://md.research.elamur.ai/free/en/papers/ling-2016-latent-predictor-networks-code-generation/) 1. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/) 2. [**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/) 3. [**Pointer Sentinel Mixture Models arXiv:1609.07843**Stephen Merity, Caiming Xiong, James Bradbury, et al.*2016 · 1,733 citations*](https://md.research.elamur.ai/free/en/papers/merity-2016-pointer-sentinel-mixture-models/) 4. **[Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task](https://md.research.elamur.ai/free/en/papers/yu-2018-spider-large-scale-human-labeled/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tao Yu, Rui Zhang, Kai Yang, et al.*2018 · 1,602 citations* 5. [**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/) 6. **[Sentence Simplification with Deep Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zhang-2017-sentence-simplification-deep-reinforcement-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xingxing Zhang, Mirella Lapata*2017 · 568 citations* 7. **[A Network-based End-to-End Trainable Task-oriented Dialogue System](https://md.research.elamur.ai/free/en/papers/wen-2017-network-based-end-end-trainable/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tsung-Hsien Wen, David Vandyke, Nikola Mrkšić, et al.*2017 · 534 citations* 8. [**Measuring Coding Challenge Competence With APPS arXiv:2105.09938**Dan Hendrycks, Steven Basart, Saurav Kadavath, et al.*2021 · 457 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-measuring-coding-challenge-competence-apps/) 9. **[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* 10. **[Self-planning Code Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2023-self-planning-code-generation-large/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Xue Jiang, Yihong Dong, Lecheng Wang, et al.*2023 · 223 citations* 11. **[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* 12. **[Insertion-based Decoding with Automatically Inferred Generation Order](https://md.research.elamur.ai/free/en/papers/gu-2019-insertion-based-decoding-automatically-inferred/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiatao Gu, Qi Liu, Kyunghyun Cho*2019 · 125 citations* 13. **[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* 14. [**SPoC: Search-based Pseudocode to Code arXiv:1906.04908**Sumith Kulal, Panupong Pasupat, Kartik Chandra, et al.*2019 · 96 citations*](https://md.research.elamur.ai/free/en/papers/kulal-2019-spoc-search-based-pseudocode-code/) 15. **[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* 16. **[DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset](https://md.research.elamur.ai/free/en/papers/wang-2020-dusql-large-scale-pragmatic-chinese/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lijie Wang, Ao Zhang, Kun Wu, et al.*2020 · 64 citations* 17. **[Deep Learning Based Code Generation Methods: Literature Review (基于深度学习的代码生成方法研究进展)](https://md.research.elamur.ai/free/en/papers/yang-2023-deep-learning-code/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Zezhou Yang (杨泽洲), Sirong Chen (陈思榕), Cuiyun Gao (高翠芸), et al.*2023 · 1 citation* 18. **[Survey on Code Generation with LLM-based Agents (基于大语言模型智能体的代码生成综述)](https://md.research.elamur.ai/free/en/papers/dong-2025-code-generation-llm/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yihong Dong (董益宏), Xue Jiang (姜雪), Jiaru Qian (钱家如), et al.*2025* 86 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/ling-2016-latent-predictor-networks-code-generation/) — Latent Predictor Networks for Code Generation