Summary of Smartagent: Chain-of-user-thought For Embodied Personalized Agent in Cyber World, by Jiaqi Zhang et al.
SmartAgent: Chain-of-User-Thought for Embodied Personalized Agent in Cyber World
by Jiaqi Zhang, Chen Gao, Liyuan Zhang, Yong Li, Hongzhi Yin
First submitted to arxiv on: 10 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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Summary difficulty | Written by | Summary |
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High | Paper authors | High Difficulty Summary Read the original abstract here |
Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes Chain-of-User-Thought (COUT), a novel embodied reasoning paradigm that incorporates personalized factors into autonomous agent learning. The authors introduce SmartAgent, an agent framework that perceives cyber environments and reasons personalized requirements through interactions with GUIs and item pools. To demonstrate SmartAgent’s capabilities, the authors create a brand-new dataset called SmartSpot, which offers a full-stage personalized action-involved environment. This paper is the first to formulate the COUT process and serves as a preliminary attempt towards embodied personalized agent learning. |
Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about creating an intelligent robot that can help people make decisions in complex situations. The current robots are good at following rules, but they don’t understand what people want. To fix this, the authors created a new way for the robot to think about what people want by considering their past actions and preferences. They also created a special set of data called SmartSpot that lets them test how well their robot works. |