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arXiv — cs.AI

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Заголовок на английскомThe Trinity:Capability-Driven Recursive Self-Improvement for Multimodal Agents

arXiv:2610.36077v1 Announce Type: new Abstract: Multimodal intelligence can be viewed as human-guided co-evolution between worlds and agents through interaction. However, scaling this process faces two bottlenecks: constructing heterogeneous, verifiable environments is costly,…

arXiv — cs.AIАвтор: Weidong Tang, Ruiheng Wang, Jingxuan Zhang, Hexin Wang, Haoyuan Chen, Zhengfeiyang Zhang, Yixing Ma, Zichen Jiang, Ziyu Guo, Haodong Li, Zhengbo Jiao, Zhiqing Cui, Xinxiang Yin, Shuo Liang, Zhenglin Wan, Hongzhan Lin, Wangbo Zhao Kaipeng Zhang, Pengfei Zhou, Odin Zhang, Yang You28 октября 2026 г. (13 часов назад)
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Кратко от AI: Главные тезисы

  • arXiv:2610.36077v1 Announce Type: new Abstract: Multimodal intelligence can be viewed as human-guided co-evolution between worlds and agents through interaction
  • However, scaling this process faces two bottlenecks: constructing heterogeneous, verifiable environments is costly,…
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The Trinity:Capability-Driven Recursive Self-Improvement for Multimodal Agents

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