--- title: "Who cites BabyAI: A Platform to Study the — 60 citing papers" description: "60 papers of the Elamur Research library cite «BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning», found in…" canonical: "https://research.elamur.ai/free/en/papers/chevalier-boisvert-2018-babyai-platform-study-sample-efficiency/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/chevalier-boisvert-2018-babyai-platform-study-sample-efficiency/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [BabyAI: A Platform to Study the Sample Efficiency…](https://md.research.elamur.ai/free/en/papers/chevalier-boisvert-2018-babyai-platform-study-sample-efficiency/) / cited by # Who cites «BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning» 60 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning»](https://md.research.elamur.ai/free/en/papers/chevalier-boisvert-2018-babyai-platform-study-sample-efficiency/) 1. **[Language Models as Knowledge Bases?](https://md.research.elamur.ai/free/en/papers/petroni-2019-language-models-as-knowledge-bases/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, et al.*2019 · 3,028 citations* 2. **[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* 3. [**MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge arXiv:2206.08853**Linxi Fan, Guanzhi Wang, Yunfan Jiang, et al.*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/fan-2022-minedojo-building-open-ended-embodied/) 4. **[AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents](https://md.research.elamur.ai/free/en/papers/ma-2024-agentboard-analytical-evaluation-board-multi/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chang Ma, Junlei Zhang, Zhihao Zhu, et al.*2024 · 90 citations* 5. [**AI Agents That Matter arXiv:2407.01502**Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel, et al.*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/kapoor-2024-ai-agents-that-matter/) 6. [**COLLIE: Systematic Construction of Constrained Text Generation Tasks arXiv:2307.08689**Shunyu Yao, Howard Chen, Austin W. Hanjie, et al.*2023 · 23 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-collie-systematic-construction-constrained-text/) 7. **[Draw Me a Flower: Processing and Grounding Abstraction in Natural Language](https://md.research.elamur.ai/free/en/papers/lachmy-2022-draw-me-flower-processing-grounding/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Royi Lachmy, Valentina Pyatkin, Avshalom Manevich, et al.*2022 · 21 citations* 8. **[Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents](https://md.research.elamur.ai/free/en/papers/yu-2026-agentic-memory-learning-unified-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Yu, Liuyi Yao, Yuexiang Xie, et al.*2026 · 6 citations* 9. **[Agentic Episodic Control](https://md.research.elamur.ai/free/en/papers/yang-2026-agentic-episodic-control/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xidong Yang, Wenhao Li, Junjie Sheng, et al.*2026* 10. **[Self-Guided Plan Extraction for Instruction-Following Tasks with Goal-Conditional Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/volovikova-2026-self-guided-plan-extraction-instruction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zoya Volovikova, Nikita Sorokin, Dmitriy Lukashevskiy, et al.*2026* 11. **[The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check](https://md.research.elamur.ai/free/en/papers/lu-2026-bitter-lesson-diffusion-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingyu Lu, Liang Ding, Kanjian Zhang, et al.*2026* 49 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/chevalier-boisvert-2018-babyai-platform-study-sample-efficiency/) — BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning