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This work introduces a bottom-up forum framework inspired by Philosophy for Children, in which language-model agents read a philosophical narrative, propose and select questions, and develop a shared conclusion without a privileged model facilitator or aggregator.
A new view of self-improving agentic systems: progress can be driven primarily by the curated persistent knowledge, which is contained in the knowledge rather than the agent, and improvement can be more inspectable, transferable, and portable.
V ENDI E VOLVE augments LLM-guided evolutionary search with label-free distributional diversity signals that diagnose population-level collapse and keep semantically distinct programs influential as context for future LLM mutations.
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