Same physical state, different collective dynamics: state encodings select synchronization outcomes in language-model agents
arXiv:2608.06968v1 Announce Type: cross Abstract: Language-model agents act on state encodings of their environment, yet these are treated as interchangeable interfaces. Using pretrained language models, we designed a circular-synchronization experiment applying a state-encoding intervention while holding the physical system fixed: each agent sees only a summary of its neighbours' relative phases and chooses to advance, stay or retard. Encoding that state as low-order circular moments rather tha
Record details
Published: 10 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Agents & autonomy · Environment
Retrieved: 10 August 2026
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ethics.ai (10 August 2026), “Same physical state, different collective dynamics: state encodings select synchronization outcomes in language-model agents,” evidence record 17764, https://ethics.ai/record/17764 (originally published by arXiv cs.CY).
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