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DeepMind Lab

arXiv 1612.03801 ↗First posted 12 Dec 2016cs.AIcited by 74

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Abstract (arXiv)

DeepMind Lab is a first-person 3D game platform designed for research and development of general artificial intelligence and machine learning systems. DeepMind Lab can be used to study how autonomous artificial agents may learn complex tasks in large, partially observed, and visually diverse worlds. DeepMind Lab has a simple and flexible API enabling creative task-designs and novel AI-designs to be explored and quickly iterated upon. It is powered by a fast and widely recognised game engine, and tailored for effective use by the research community.

Key facts. Cited by 74 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Dec 2016.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 15; 2022: 13; 2023: 12; 2024: 14; 2025: 12; 2026: 8.

74 papers.

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  1. 2022Visual Prompt Tuningcited by 1,681
  2. 2021A Survey of Embodied AI: From Simulators to Research Taskscited by 261
  3. 2025A Survey on Vision-Language-Action Models: An Action Tokenization Perspectivecited by 96
  4. 2021The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark for Physically Realistic Embodied AIcited by 65
  5. 2023A Survey of Temporal Credit Assignment in Deep Reinforcement Learningcited by 59
  6. 2021Counter-Strike Deathmatch with Large-Scale Behavioural Cloningcited by 50
  7. 2023Gradient-based Parameter Selection for Efficient Fine-Tuningcited by 40
  8. 2021CORA: Benchmarks, Baselines, and Metrics as a Platform for Continual Reinforcement Learning Agentscited by 38
  9. 2022On Transforming Reinforcement Learning by Transformer: The Development Trajectorycited by 36
  10. 2021Autonomous Reinforcement Learning: Formalism and Benchmarkingcited by 33
  11. 20213DB: A Framework for Debugging Computer Vision Modelscited by 31
  12. 2021Core Challenges in Embodied Vision-Language Planningcited by 30
38 more
  1. 2026GameWorld: Towards Standardized and Verifiable Evaluation of Multimodal Game Agentscited by 28
  2. 2024Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey and Benchmarkcited by 23
  3. 2021Capturing the objects of vision with neural networkscited by 21
  4. 2023SCT: A Simple Baseline for Parameter-Efficient Fine-Tuning via Salient Channelscited by 20
  5. 2022The Health Gym: Synthetic Health-Related Datasets for the Development of Reinforcement Learning Algorithmscited by 19
  6. 2025A Survey of Continual Reinforcement Learningcited by 18
  7. 2021Teaching Agents how to Map: Spatial Reasoning for Multi-Object Navigationcited by 17
  8. 2022Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worldscited by 17
  9. 2024PYRA: Parallel Yielding Re-Activation for Training-Inference Efficient Task Adaptationcited by 17
  10. 2021Sample-efficient Reinforcement Learning Representation Learning with Curiosity Contrastive Forward Dynamics Modelcited by 16
  11. 2023Games for Artificial Intelligence Research: A Review and Perspectivescited by 14
  12. 2022Learning to Generalize with Object-centric Agents in the Open World Survival Game Craftercited by 13
  13. 2024A Review of Nine Physics Engines for Reinforcement Learning Researchcited by 12
  14. 2023ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learningcited by 11
  15. 2026VisGym: Diverse, Customizable, Scalable Environments for Multimodal Agentscited by 11
  16. 2023SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand Corescited by 10
  17. 2024Normalizing Flow-based Differentiable Particle Filterscited by 10
  18. 2024World Models: The Safety Perspectivecited by 9
  19. 2021Communicative Learning with Natural Gestures for Embodied Navigation Agents with Human-in-the-Scenecited by 7
  20. 2023Graph schemas as abstractions for transfer learning, inference, and planningcited by 7
  21. 2022Consistent Attack: Universal Adversarial Perturbation on Embodied Vision Navigationcited by 6
  22. 2023MoSA: Mixture of Sparse Adapters for Visual Efficient Tuningcited by 6
  23. 2024Token Compensator: Altering Inference Cost of Vision Transformer without Re-Tuningcited by 6
  24. 2026Data Pyramid for Embodied Manipulation: A Surveycited by 6
  25. 2021Graph augmented Deep Reinforcement Learning in the GameRLand3D environmentcited by 5
  26. 2022Mask Atari for Deep Reinforcement Learning as POMDP Benchmarkscited by 5
  27. 2021Godot Reinforcement Learning Agentscited by 4
  28. 2022Compositional Generalization in Grounded Language Learning via Induced Model Sparsitycited by 4
  29. 2022Lamarckian Platform: Pushing the Boundaries of Evolutionary Reinforcement Learning towards Asynchronous Commercial Gamescited by 4
  30. 2024SPARO: Selective Attention for Robust and Compositional Transformer Encodings for Visioncited by 4
  31. 2024Benchmarking Deep Reinforcement Learning for Navigation in Denied Sensor Environmentscited by 4
  32. 2024ALoRE: Efficient Visual Adaptation via Aggregating Low Rank Expertscited by 4
  33. 2026SPEAR: A Simulator for Photorealistic Embodied AI Researchcited by 4
  34. 2021rl_reach: Reproducible Reinforcement Learning Experiments for Robotic Reaching Taskscited by 3
  35. 2026A Reference Architecture of Reinforcement Learning Frameworkscited by 3
  36. 2021Messing Up 3D Virtual Environments: Transferable Adversarial 3D Objectscited by 2
  37. 2024iDAT: inverse Distillation Adapter-Tuningcited by 2
  38. 2024Revisiting semi-supervised training objectives for differentiable particle filterscited by 2

50 most cited of 74 All 74 (JSON)