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Local Predictability and Collective Fidelity in LLM-Agent Societies
II

Igor Itkin

· 1 min read

ResearcharXiv cs.AI

Local Predictability and Collective Fidelity in LLM-Agent Societies

arXiv:2609.35813v1 Announce Type: cross Abstract: Compact surrogates could reduce the cost of simulating large language model societies, but must reproduce collective behavior. We compare individual predictions and collective forecasts using 9,455 published trajectories and new experiments on opinion dynamics. Neighbor information improves individual prediction in all 16 public-data settings and pooled collective forecasts on held-out questions, although collective gains depend on transfer conditions. Tests on 24 new statements do not confirm earlier contrasting history effects in forecasts from the initial state. Qwen benefits from history after three observed rounds. These findings motivate direct collective validation, explicit limits on available observations, and comparisons with simple baselines.

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This story was published by arXiv cs.AI and written by Igor Itkin. SyncAI.news shows a preview; the complete article is on the publisher's site.

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