mlsanityData to 7 Oct 2026

BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning

arXiv 1810.08272 ↗First posted 18 Oct 2018cs.AI cs.CLcited by 238

Not on the map. Why?

Cited by 62 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Allowing humans to interactively train artificial agents to understand language instructions is desirable for both practical and scientific reasons, but given the poor data efficiency of the current learning methods, this goal may require substantial research efforts. Here, we introduce the BabyAI research platform to support investigations towards including humans in the loop for grounded language learning. The BabyAI platform comprises an extensible suite of 19 levels of increasing difficulty. The levels gradually lead the agent towards acquiring a combinatorially rich synthetic language which is a proper subset of English. The platform also provides a heuristic expert agent for the purpose of simulating a human teacher. We report baseline results and estimate the amount of human involvement that would be required to train a neural network-based agent on some of the BabyAI levels. We put forward strong evidence that current deep learning methods are not yet sufficiently sample efficient when it comes to learning a language with compositional properties.

Key facts. Cited by 238 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Oct 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2019: 1; 2020: 3; 2021: 28; 2022: 30; 2023: 31; 2024: 38; 2025: 51; 2026: 56.

238 papers.

Sort:

By area:

  1. 2022A Generalist Agentcited by 802
  2. 2022MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledgecited by 469
  3. 2023Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Taskscited by 320
  4. 2024AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agentscited by 319
  5. 2025Memory in the Age of AI Agentscited by 285
  6. 2020Language Conditioned Imitation Learning over Unstructured Datacited by 208
  7. 2024AI Agents That Mattercited by 199
  8. 2023Grounding Large Language Models in Interactive Environments with Online Reinforcement Learningcited by 193
  9. 2021A Survey of Zero-shot Generalisation in Deep Reinforcement Learningcited by 164
  10. 2023Foundation Models for Decision Making: Problems, Methods, and Opportunitiescited by 160
  11. 2024Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoningcited by 136
  12. 2025Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memorycited by 129
38 more
  1. 2024AgentGym: Evolving Large Language Model-based Agents across Diverse Environmentscited by 120
  2. 2021Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotationcited by 117
  3. 2024A Survey on Large Language Model-Based Game Agentscited by 106
  4. 2024HiAgent: Hierarchical Working Memory Management for Solving Long-Horizon Agent Tasks with Large Language Modelcited by 101
  5. 2019Help, Anna! Visual Navigation with Natural Multimodal Assistance via Retrospective Curiosity-Encouraging Imitation Learningcited by 100
  6. 2023Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysiscited by 99
  7. 2023LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Modelscited by 84
  8. 2024AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generationcited by 80
  9. 2026Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agentscited by 72
  10. 2023COLLIE: Systematic Construction of Constrained Text Generation Taskscited by 69
  11. 2025AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learningcited by 68
  12. 2023"No, to the Right" -- Online Language Corrections for Robotic Manipulation via Shared Autonomycited by 60
  13. 2021Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learningcited by 53
  14. 2022Retrieval-Augmented Reinforcement Learningcited by 53
  15. 2025AgentRefine: Enhancing Agent Generalization through Refinement Tuningcited by 51
  16. 2022Improving Intrinsic Exploration with Language Abstractionscited by 49
  17. 2026AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applicationscited by 46
  18. 2023Read and Reap the Rewards: Learning to Play Atari with the Help of Instruction Manualscited by 45
  19. 2021Grounding 'Grounding' in NLPcited by 44
  20. 2021ELLA: Exploration through Learned Language Abstractioncited by 42
  21. 2021Word Acquisition in Neural Language Modelscited by 41
  22. 2022Contrastive language and vision learning of general fashion conceptscited by 41
  23. 2023Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Predictioncited by 39
  24. 2021Learning General Optimal Policies with Graph Neural Networks: Expressive Power, Transparency, and Limitscited by 38
  25. 2025Large Language Models for Planning: A Comprehensive and Systematic Surveycited by 38
  26. 2024True Knowledge Comes from Practice: Aligning LLMs with Embodied Environments via Reinforcement Learningcited by 36
  27. 2025Memory, Benchmark & Robots: A Benchmark for Solving Complex Tasks with Reinforcement Learningcited by 34
  28. 2024LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrationscited by 32
  29. 2023Bridging RL Theory and Practice with the Effective Horizoncited by 31
  30. 2022LISA: Learning Interpretable Skill Abstractions from Languagecited by 30
  31. 2025ATLaS: Agent Tuning via Learning Critical Stepscited by 29
  32. 2023Enabling Intelligent Interactions between an Agent and an LLM: A Reinforcement Learning Approachcited by 28
  33. 2024LLM-Empowered State Representation for Reinforcement Learningcited by 28
  34. 2024EPO: Hierarchical LLM Agents with Environment Preference Optimizationcited by 28
  35. 2021A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learningcited by 27
  36. 2021LILA: Language-Informed Latent Actionscited by 27
  37. 2021Interactive Learning from Activity Descriptioncited by 26
  38. 2024Odyssey: Empowering Minecraft Agents with Open-World Skillscited by 26

50 most cited of 238 All 238 (JSON)