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Detailed balance in large language model-driven agents
adaptation-and-self-organizing-systemsartificial-intelligencedata-analysismachine-learningstatistical-mechanicsstatistics-and-probability
Large language model (LLM)-driven agents are emerging as a powerful new paradigm for solving complex problems. Despite the empirical success of these practices, a theoretical framework to understand and unify their macroscopic dynamics remains lacking. This paper proposes a method based on the least
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