mlsanityData to 14 Oct 2026

Advances and Innovations in the Multi-Agent Robotic System (MARS) Challenge

arXiv 2601.18733 ↗First posted 26 Jan 2026cs.RO cs.AI cs.CVcited by 1

On the map: Multimodal LLMs / vision-language models → Embodied and 3D vision-language models

also in 1 more
Abstract (arXiv)

Recent advancements in multimodal large language models and vision-languageaction models have significantly driven progress in Embodied AI. As the field transitions toward more complex task scenarios, multi-agent system frameworks are becoming essential for achieving scalable, efficient, and collaborative solutions. This shift is fueled by three primary factors: increasing agent capabilities, enhancing system efficiency through task delegation, and enabling advanced human-agent interactions. To address the challenges posed by multi-agent collaboration, we propose the Multi-Agent Robotic System (MARS) Challenge, held at the NeurIPS 2025 Workshop on SpaVLE. The competition focuses on two critical areas: planning and control, where participants explore multi-agent embodied planning using vision-language models (VLMs) to coordinate tasks and policy execution to perform robotic manipulation in dynamic environments. By evaluating solutions submitted by participants, the challenge provides valuable insights into the design and coordination of embodied multi-agent systems, contributing to the future development of advanced collaborative AI systems.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Embodied and 3D vision-language models, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 37 of its 40 references that are in the map. First posted on arXiv 26 Jan 2026.

Builds on

37 of 40 references.

Closest ancestors · 4

Same direction, newest first

  1. 2025VIKI-R: Coordinating Embodied Multi-Agent Cooperation via Reinforcement Learning10 Jun
  2. 2025Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success27 Feb
  3. 2025DexVLA: Vision-Language Model with Plug-In Diffusion Expert for General Robot Control9 Feb
  4. 2023RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control28 Jul

Other references · 33

  1. 2024OpenVLA: An Open-Source Vision-Language-Action Modelcited by 2,887
  2. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,838
  3. 2024π0: A Vision-Language-Action Flow Model for General Robot Controlcited by 2,407
  4. 2022RT-1: Robotics Transformer for Real-World Control at Scalecited by 2,061
  5. 2025Gemma 3 Technical Reportcited by 1,824
  6. 2025π0.5: a Vision-Language-Action Model with Open-World Generalizationcited by 1,761
  7. 2024Octo: An Open-Source Generalist Robot Policycited by 1,484
  8. 2024RDT-1B: a Diffusion Foundation Model for Bimanual Manipulationcited by 691
  9. 2025RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulationcited by 518
  10. 2024CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulationcited by 422
  11. 2024RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robotscited by 407
  12. 2019On the Utility of Learning about Humans for Human-AI Coordinationcited by 349
21 more
  1. 2024Latent Action Pretraining from Videoscited by 321
  2. 20243D Diffuser Actor: Policy Diffusion with 3D Scene Representationscited by 282
  3. 2023Building Cooperative Embodied Agents Modularly with Large Language Modelscited by 237
  4. 2024ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AIcited by 229
  5. 2023RoCo: Dialectic Multi-Robot Collaboration with Large Language Modelscited by 172
  6. 2023AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Plannerscited by 149
  7. 2020Watch-And-Help: A Challenge for Social Perception and Human-AI Collaborationcited by 133
  8. 2025GR-3 Technical Reportcited by 111
  9. 2024PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-agent Taskscited by 82
  10. 2023SkillDiffuser: Interpretable Hierarchical Planning via Skill Abstractions in Diffusion-Based Task Executioncited by 70
  11. 2023LLM-Coordination: Evaluating and Analyzing Multi-agent Coordination Abilities in Large Language Modelscited by 68
  12. 2020A Cordial Sync: Going Beyond Marginal Policies for Multi-Agent Embodied Taskscited by 52
  13. 2024RISE: 3D Perception Makes Real-World Robot Imitation Simple and Effectivecited by 41
  14. 2024LLaMAR: Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environmentscited by 32
  15. 2025RoboFactory: Exploring Embodied Agent Collaboration with Compositional Constraintscited by 31
  16. 2025RoboOS: A Hierarchical Embodied Framework for Cross-Embodiment and Multi-Agent Collaborationcited by 28
  17. 2024LiP-LLM: Integrating Linear Programming and dependency graph with Large Language Models for multi-robot task planningcited by 24
  18. 2024DART-LLM: Dependency-Aware Multi-Robot Task Decomposition and Execution using Large Language Modelscited by 19
  19. 2024DexHandDiff: Interaction-aware Diffusion Planning for Adaptive Dexterous Manipulationcited by 15
  20. 2025Multi-Agent LLM Actor-Critic Framework for Social Robot Navigationcited by 8
  21. 2025RoboBallet: Planning for Multi-Robot Reaching with Graph Neural Networks and Reinforcement Learningcited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Ego to World: Collaborative Spatial Reasoning in Embodied Systems via Reinforcement Learningcited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2025Transforming Monolithic Foundation Models into Embodied Multi-Agent Architectures for Human-Robot Collaboration
  2. 2025MARS: Multi-Agent Robotic System with Multimodal Large Language Models for Assistive Intelligence
  3. 2026When Multi-Robot Systems Meet Agentic AI:Towards Embodied Collective Intelligence
  4. 2025Towards Embodied Agentic AI: Review and Classification of LLM- and VLM-Driven Robot Autonomy and Interaction
  5. 2024MALMM: Multi-Agent Large Language Models for Zero-Shot Robotics Manipulation
  6. 2025REMAC: Self-Reflective and Self-Evolving Multi-Agent Collaboration for Long-Horizon Robot Manipulation
  7. 2025Using Language Models as Closed-Loop High-Level Planners for Robotics Applications: A Brief Overview and Benchmarks
  8. 2026Systematic Multi-Agent Vision-and-Language Navigation: Formulation, Benchmark, and Method