mlsanityData to 14 Oct 2026

Two Body Problem: Collaborative Visual Task Completion

arXiv 1904.05879 ↗First posted 11 Apr 2019cs.CV cs.AI cs.MAcited by 45

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Abstract (arXiv)

Collaboration is a necessary skill to perform tasks that are beyond one agent's capabilities. Addressed extensively in both conventional and modern AI, multi-agent collaboration has often been studied in the context of simple grid worlds. We argue that there are inherently visual aspects to collaboration which should be studied in visually rich environments. A key element in collaboration is communication that can be either explicit, through messages, or implicit, through perception of the other agents and the visual world. Learning to collaborate in a visual environment entails learning (1) to perform the task, (2) when and what to communicate, and (3) how to act based on these communications and the perception of the visual world. In this paper we study the problem of learning to collaborate directly from pixels in AI2-THOR and demonstrate the benefits of explicit and implicit modes of communication to perform visual tasks. Refer to our project page for more details: https://prior.allenai.org/projects/two-body-problem

Key facts. Cited by 45 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Apr 2019.

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Citing papers per year: 2021: 14; 2022: 7; 2023: 18; 2024: 2; 2025: 2; 2026: 2.

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  1. 2022ProcTHOR: Large-Scale Embodied AI Using Procedural Generationcited by 380
  2. 2021A Survey of Embodied AI: From Simulators to Research Taskscited by 261
  3. 2023Building Cooperative Embodied Agents Modularly with Large Language Modelscited by 237
  4. 2023Habitat 3.0: A Co-Habitat for Humans, Avatars and Robotscited by 228
  5. 2023Affordances from Human Videos as a Versatile Representation for Roboticscited by 226
  6. 2021Simple but Effective: CLIP Embeddings for Embodied AIcited by 191
  7. 2021Visual Room Rearrangementcited by 102
  8. 2022SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learningcited by 95
  9. 2023PIRLNav: Pretraining with Imitation and RL Finetuning for ObjectNavcited by 93
  10. 2023MindAgent: Emergent Gaming Interactioncited by 88
  11. 2023ARNOLD: A Benchmark for Language-Grounded Task Learning With Continuous States in Realistic 3D Scenescited by 69
  12. 2023LLM-Coordination: Evaluating and Analyzing Multi-agent Coordination Abilities in Large Language Modelscited by 68
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  1. 2021Cooperative Exploration for Multi-Agent Deep Reinforcement Learningcited by 57
  2. 2022Retrospectives on the Embodied AI Workshopcited by 46
  3. 2022AssistQ: Affordance-centric Question-driven Task Completion for Egocentric Assistantcited by 32
  4. 2023Towards A Holistic Landscape of Situated Theory of Mind in Large Language Modelscited by 32
  5. 2024LLaMAR: Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environmentscited by 32
  6. 2023Pretrained Language Models as Visual Planners for Human Assistancecited by 28
  7. 2021The Surprising Effectiveness of Visual Odometry Techniques for Embodied PointGoal Navigationcited by 27
  8. 2022Last-Mile Embodied Visual Navigationcited by 25
  9. 2021GridToPix: Training Embodied Agents with Minimal Supervisioncited by 21
  10. 2023HandMeThat: Human-Robot Communication in Physical and Social Environmentscited by 20
  11. 2021Learning Efficient Multi-Agent Cooperative Visual Explorationcited by 19
  12. 2021Interpretation of Emergent Communication in Heterogeneous Collaborative Embodied Agentscited by 19
  13. 2021Collaborative Visual Navigationcited by 18
  14. 2021Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learningcited by 18
  15. 2021Shaping embodied agent behavior with activity-context priors from egocentric videocited by 17
  16. 2023Adaptive Coordination in Social Embodied Rearrangementcited by 14
  17. 2025Advancing Audio-Visual Navigation Through Multi-Agent Collaboration in 3D Environmentscited by 14
  18. 2023MOPA: Modular Object Navigation with PointGoal Agentscited by 11
  19. 2021Multi-Agent Embodied Visual Semantic Navigation with Scene Prior Knowledgecited by 10
  20. 2024Infer Human's Intentions Before Following Natural Language Instructionscited by 10
  21. 2023Exploitation-Guided Exploration for Semantic Embodied Navigationcited by 9
  22. 2023Chat2Map: Efficient Scene Mapping from Multi-Ego Conversationscited by 8
  23. 2023LEMMA: Learning Language-Conditioned Multi-Robot Manipulationcited by 7
  24. 2021Visual Perspective Taking for Opponent Behavior Modelingcited by 6
  25. 2023Heterogeneous Embodied Multi-Agent Collaborationcited by 6
  26. 2022CH-MARL: A Multimodal Benchmark for Cooperative, Heterogeneous Multi-Agent Reinforcement Learningcited by 4
  27. 2023Moving Forward by Moving Backward: Embedding Action Impact over Action Semanticscited by 3
  28. 2021Deep Learning for Embodied Vision Navigation: A Surveycited by 2
  29. 2026Unified Visuomotor Targets: Supervising VLAs Beyond Physical Actionscited by 2
  30. 2022ASC me to Do Anything: Multi-task Training for Embodied AIcited by 1
  31. 2023Cooperative Multi-Agent Learning for Navigation via Structured State Abstractioncited by 1
  32. 2025From Grunts to Lexicons: Emergent Language from Cooperative Foragingcited by 1
  33. 2026Token Communication-Assisted Collaborative Embodied Artificial Intelligence: Concepts, Framework, and Opportunitiescited by 0