Ella: Embodied Social Agents with Lifelong Memory

Hongxin Zhang, Zheyuan Zhang, Zeyuan Wang, Zunzhe Zhang, Lixing Fang +2 more
6/30/2025
cs.CVcs.CL

No official code found. Best implementation: UMass-Embodied-AGI/Ella (18 stars, last commit 2026-02-04).

Abstract

We introduce Ella, an embodied social agent capable of lifelong learning within a community in a 3D open world, where agents accumulate experiences and acquire knowledge through everyday visual observations and social interactions. At the core of Ella's capabilities is a structured, long-term multimodal memory system that stores, updates, and retrieves information effectively. It consists of a name-centric semantic memory for organizing acquired knowledge and a spatiotemporal episodic memory for capturing multimodal experiences. By integrating this lifelong memory system with foundation models, Ella retrieves relevant information for decision-making, plans daily activities, builds social relationships, and evolves autonomously while coexisting with other intelligent beings in the open world. We conduct capability-oriented evaluations in a dynamic 3D open world where 15 agents engage in social activities for days and are assessed with a suite of unseen controlled evaluations. Experimental results show that Ella can influence, lead, and cooperate with other agents well to achieve goals, showcasing its ability to learn effectively through observation and social interaction. Our findings highlight the transformative potential of combining structured memory systems with foundation models for advancing embodied intelligence. More videos can be found at https://umass-embodied-agi.github.io/Ella/.

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Source codes for the paper "Ella: Embodied Social Agents with Lifelong Memory"

183C++, ShellJun 30, 20258 months ago
agentembodied-ai

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Cite this paper

@article{zhang2025ella,
  title  = {Ella: Embodied Social Agents with Lifelong Memory},
  author = {Hongxin Zhang and Zheyuan Zhang and Zeyuan Wang and Zunzhe Zhang and Lixing Fang and Qinhong Zhou and Chuang Gan},
  year   = {2025},
  eprint = {2506.24019},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2506.24019v1}
}

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