NEmo: Neuro-Symbolic Embodied Intelligence

Recent advances in embodied AI increasingly rely on the integration of neural perception, symbolic reasoning, and large language models (LLMs) to support robust decision-making in complex environments. Yet, significant challenges remain in enabling agents to operate reliably over long horizons, revise their internal knowledge structures from experience, and maintain interpretable and transferable representations of the world. This workshop explores emerging neuro-symbolic approaches for embodied intelligence, with a focus on long-horizon planning, self-evolving agents, trustworthy integration of LLMs, and reliable knowledge management. Particular attention is devoted to the development of interoperable semantic representations that connect perception, affordances, planning, and execution across robotic systems. By bringing together researchers from neuro-symbolic AI, robotics, machine learning, knowledge representation, and embodied reasoning, the workshop aims to identify open challenges, share methodologies, and foster a research agenda for scalable and trustworthy embodied neuro-symbolic systems.