Self-play LLM trajectories form model-specific attractors that asymmetrically influence mixed-play partners' stylistic choices and stances across 7 models and 20 topics.
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Authors define EASE as a modular architecture for LLM multi-agent simulations, implement it in the SiliSocS sandbox, and illustrate its use via three case studies on research questions in generated social scenarios.
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Attractor States Emerge in Multi-Turn LLM Conversations
Self-play LLM trajectories form model-specific attractors that asymmetrically influence mixed-play partners' stylistic choices and stances across 7 models and 20 topics.