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Identity as Attractor: Geometric Evidence for Persistent Agent Architecture in LLM Activation Space

ArXiv CS.AI15 Apr
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Researchers discovered that large language models exhibit attractor-like behavior for agent identities, similar to how they handle semantic relationships. This suggests LLMs could support persistent cognitive agents with stable internal representations, advancing our understanding of emergent agent-like behavior in neural networks.

LLMs may maintain persistent agent identities through attractor-like dynamics in activation space.

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