Persistent notebook memory enables reliable language emergence in LLM agents across channel capacities, outperforming stateless and rolling-context setups in Lewis signaling games.
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From Signals to Structure: How Memory Architecture Drives Language Emergence in LLM Agents
Persistent notebook memory enables reliable language emergence in LLM agents across channel capacities, outperforming stateless and rolling-context setups in Lewis signaling games.