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About this paper
Yongheng Zhang, Ziang Liu, Jiaxuan Zhu, Shuai Wang, Xiangqi Chen, Haojing Huang, Jiayi Kuang, Siyu Chen and 12 more
A comprehensive survey from Tencent Youtu Lab, Tsinghua University, and others outlines the evolution of Large Language Models (LLMs) from conversational agents to persistent autonomous AI. It introduces a "Workspace + Skill" paradigm to enable reliable task completion and digital collaboration, detailing the necessary shifts in cognitive core capabilities, task execution, and evaluation methodologies toward verifiable task closure.
Key insights
- LLMs are transforming from 'fast thinking' chatbots to 'slow thinking' deliberate reasoners, capable of multi-step problem-solving and self-correction through inference-time computation.
- The combination of persistent 'Workspaces' and reusable 'Skills' is crucial for transitioning LLMs from episodic tool use to robust, persistent, and verifiable autonomous task execution.
- Reliable autonomous AI development mandates a redefinition of evaluation, moving from final output accuracy to process-level judgment and, ultimately, end-to-end task closure metrics in interactive environments.
Summary by alphaXiv.
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