paperSeptember 2026Unreviewed

GlossoGen: Emergent Language in Complex Multi-Agent LLM Interactions

Elias Stengel-Eskin, Newton Sander, Carlos Bonetti, Sasha Boguraev, James Bowler, Hale Sirin, Simon Kirby

Abstract

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 fin

Cite

@misc{stengeleskin2026glossogen,
  title = {{GlossoGen: Emergent Language in Complex Multi-Agent LLM Interactions}},
  author = {Elias Stengel-Eskin and Newton Sander and Carlos Bonetti and Sasha Boguraev and James Bowler and Hale Sirin and Simon Kirby},
  year = {2026},
  month = sep,
  eprint = {2609.01491},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.01491}
}