--- title: "Who cites Language Understanding for — 95 citing papers" description: "95 papers of the Elamur Research library cite «Language Understanding for Text-based Games Using Deep Reinforcement Learning», found…" canonical: "https://research.elamur.ai/free/en/papers/narasimhan-2015-language-understanding-text-based-games/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/narasimhan-2015-language-understanding-text-based-games/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Language Understanding for Text-based Games Using…](https://md.research.elamur.ai/free/en/papers/narasimhan-2015-language-understanding-text-based-games/) / cited by # Who cites «Language Understanding for Text-based Games Using Deep Reinforcement Learning» 95 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «Language Understanding for Text-based Games Using Deep Reinforcement Learning»](https://md.research.elamur.ai/free/en/papers/narasimhan-2015-language-understanding-text-based-games/) 1. [**Learning Transferable Visual Models From Natural Language Supervision arXiv:2103.00020**Alec Radford, Jong Wook Kim, Chris Hallacy, et al.*2021 · 8,767 citations*](https://md.research.elamur.ai/free/en/papers/radford-2021-learning-transferable-visual-models-natural/) 2. **[Deep Reinforcement Learning for Dialogue Generation](https://md.research.elamur.ai/free/en/papers/li-2016-deep-reinforcement-learning-dialogue-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiwei Li, Will Monroe, Alan Ritter, et al.*2016 · 1,502 citations* 3. **[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* 4. **[Mapping Instructions and Visual Observations to Actions with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/misra-2017-mapping-instructions-visual-observations-actions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dipendra Misra, John Langford, Yoav Artzi*2017 · 255 citations* 5. [**Learning to Speak and Act in a Fantasy Text Adventure Game arXiv:1903.03094**Jack Urbanek, Angela Fan, Siddharth Karamcheti, et al.*2019 · 243 citations*](https://md.research.elamur.ai/free/en/papers/urbanek-2019-learning-speak-act-fantasy-text/) 6. **[From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood](https://md.research.elamur.ai/free/en/papers/guu-2017-language-programs-bridging-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kelvin Guu, Panupong Pasupat, Evan Liu, et al.*2017 · 236 citations* 7. **[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* 8. [**Grounded Language Learning in a Simulated 3D World arXiv:1706.06551**Karl Moritz Hermann, Felix Hill, Simon Green, et al.*2017 · 190 citations*](https://md.research.elamur.ai/free/en/papers/hermann-2017-grounded-language-learning-simulated-3d/) 9. [**Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization arXiv:2210.01241**Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kiante Brantley, et al.*2022 · 174 citations*](https://md.research.elamur.ai/free/en/papers/ramamurthy-2022-reinforcement-learning-natural-language-processing/) 10. **[Keep CALM and Explore: Language Models for Action Generation in Text-based Games](https://md.research.elamur.ai/free/en/papers/yao-2020-keep-calm-explore-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shunyu Yao, Rohan Rao, Matthew Hausknecht, et al.*2020 · 130 citations* 11. [**Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems arXiv:1511.06931**Jesse Dodge, Andreea Gane, Xiang Zhang, et al.*2015 · 111 citations*](https://md.research.elamur.ai/free/en/papers/dodge-2015-evaluating-prerequisite-qualities-learning-end/) 12. **[Group-in-Group Policy Optimization for LLM Agent Training](https://md.research.elamur.ai/free/en/papers/feng-2025-group-group-policy-optimization-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lang Feng, Zhenghai Xue, Tingcong Liu, et al.*2025 · 69 citations* 83 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/narasimhan-2015-language-understanding-text-based-games/) — Language Understanding for Text-based Games Using Deep Reinforcement Learning