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20242026
most citedThe Landscape of Agentic Reinforcement Learning for LLMs: A Survey

1 citations · 4 across the 28 of their papers we have counts for

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cs.RO2026

Trust-Calibrated VLA Policy Post-Training with Evolving Imagination

Wenzhan Li, Yiran Qin, Heng Zhou +3

Vision-Language-Action (VLA) models are often pretrained via imitation learning, making reinforcement learning (RL) post-training important when deployment moves beyond demonstrati…

cs.RO2026

MAAP: Multi-Agent Active Perception for Collaborative Manipulation

Bruno N. Y. Chen, Li Kang, Heng Zhou +4

Multi-agent manipulation naturally produces multiple task-driven viewpoints: every arm carries a wrist camera and moves through the scene while acting. Yet these observations are t…

cs.RO2026

MA-VLA: Multi-Arm Vision-Language-Action Model for Collaboration and Compositional Generalization

Zaibin Zhang, Junlan Xiao, Zhongbo Zhang +11

Multi-arm collaboration is becoming a core capability in embodied manipulation. Recent vision-language-action (VLA) models integrate perception, language, and control, but most rep…

cs.RO2026

ComSim: Building Scalable Real-World Robot Data Generation via Compositional Simulation

Yiran Qin, Jiahua Ma, Li Kang +11

Recent advancements in foundational models, such as large language models and world models, have greatly enhanced the capabilities of robotics, enabling robots to autonomously perf…

cs.RO2026

CoEnv: Driving Embodied Multi-Agent Collaboration via Compositional Environment

Li Kang, Yutao Fan, Rui Li +11

Multi-agent embodied systems hold promise for complex collaborative manipulation, yet face critical challenges in spatial coordination, temporal reasoning, and shared workspace awa…

cs.RO2026

Ego to World: Collaborative Spatial Reasoning in Embodied Systems via Reinforcement Learning

Heng Zhou, Li Kang, Yiran Qin +12

Understanding the world from distributed, partial viewpoints is a fundamental challenge for embodied multi-agent systems. Each agent perceives the environment through an ego-centri…

cs.RO2026

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

Li Kang, Heng Zhou, Xiufeng Song +41

Recent advancements in multimodal large language models and vision-languageaction models have significantly driven progress in Embodied AI. As the field transitions toward more com…