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Persuasion in LLM networks is not just about who speaks, but how the topology and exposure shape stance shifts, revealing a complex interplay of influence that traditional analysis overlooks.
Despite advancements in LLMs, even the best agents struggle with prospective memory, achieving only 65.1% accuracy in executing delayed intentions.
