---
title: "Who cites Fumin Wang — 162 papers of our library"
description: "162 papers of the Elamur Research library cite the works of Fumin Wang, found in their bibliographies; the most cited first."
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---
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# Who cites Fumin Wang

162 citations of their works from 162 papers of our library (of the 149,439 whose bibliographies we read) · 23 with a page here, the most cited first · [← Fumin Wang](https://md.research.elamur.ai/free/en/authors/fumin-wang/)

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. [**Do As I Can, Not As I Say: Grounding Language in Robotic Affordances arXiv:2204.01691**Michael Ahn, Anthony Brohan, Noah Brown, et al.*2022 · 941 citations*](https://md.research.elamur.ai/free/en/papers/ahn-2022-i-i-say-grounding-language/)
7. **[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*
8. **[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*
9. [**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/)
10. **[TextWorld: A Learning Environment for Text-based Games](https://md.research.elamur.ai/free/en/papers/cote-2018-textworld-learning-environment-text-based/) [Communications in computer and information science](https://md.research.elamur.ai/free/en/venues/communications-in-computer-and-information-science/)**Marc-Alexandre Cote, Akos Kadar, Xingdi Yuan, et al.*2018 · 339 citations*
11. **[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*
12. **[A Survey of Reinforcement Learning Informed by Natural Language](https://md.research.elamur.ai/free/en/papers/luketina-2019-survey-reinforcement-learning-informed-natural/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Jelena Luketina, Nantas Nardelli, Gregory Farquhar, et al.*2019 · 231 citations*
13. **[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*
14. **[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*
15. **[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*
16. [**BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning arXiv:1810.08272**Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, et al.*2018 · 123 citations*](https://md.research.elamur.ai/free/en/papers/chevalier-boisvert-2018-babyai-platform-study-sample-efficiency/)
17. **[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*
18. [**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/)
19. **[A Survey of Reinforcement Learning from Human Feedback](https://md.research.elamur.ai/free/en/papers/kaufmann-2023-survey-reinforcement-learning-human-feedback/) [Transactions on Machine Learning Research](https://md.research.elamur.ai/free/en/venues/transactions-on-machine-learning-research/)**Timo Kaufmann, Paul Weng, Viktor Bengs, et al.*2023 · 92 citations*
20. **[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*
21. **[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*
22. **[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*
23. **[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*

139 more citing papers of our library have no page here yet.

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