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arXiv — cs.AI

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Governed Self-Evolution for Autonomous Investing: A Multi-Agent LLM System with an Invariant Core

arXiv:2610.30557v1 Announce Type: new Abstract: LLM agents that act on live Web data must combine heterogeneous evidence, remember what they have done and improve from outcomes without weakening their own safeguards. We study this problem in autonomous investing, where every…

arXiv — cs.AIBy: Yebo Feng, Jingyang Dai, Liangrui Pan, Nelson Lau, Jiahua Xu, Yang LiuOctober 23, 2026 (1 hour ago)
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  • arXiv:2610.30557v1 Announce Type: new Abstract: LLM agents that act on live Web data must combine heterogeneous evidence, remember what they have done and improve from outcomes without weakening their own safeguards
  • We study this problem in autonomous investing, where every…
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Governed Self-Evolution for Autonomous Investing: A Multi-Agent LLM System with an Invariant Core

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