GlossoGen: Emergent Language in Complex Multi-Agent LLM Interactions
The growing rate at which LLM agents interact with one another raises key questions about language evolution in multi-LLM-agent settings, with implications for safety and monitorability as well as for linguistic accounts of LLMs. To address these questions, we introduce GlossoGen, a novel platform for studying multi-agent language evolution in complex scenarios. Within GlossoGen, we build the SaveVeyru scenario, which requires agents with partial information to communicate under pressure. We find that language evolution does occur between LLM agents, that the resulting languages are compositio
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“Possibly related via embedding similarity 0.58 (not asserted). Timestamp check: artifact slightly before paper (-60d).”
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- FuzzySimilar title/name (fuzzy) · 59%bojieli/ai-agent-book →
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- LinkedLinked via arxiv author · 85%Elias Stengel-Eskin →
“GlossoGen: Emergent Language in Complex Multi-Agent LLM Interactions”