GlossoGen: Multi-agent spontaneous emergence of compressed language in collaborative tasks

Researchers from AE Studio, UT Austin, Schmidt Sciences, and the University of Edinburgh released the GlossoGen platform, observing in the collaborative emergency scenario SaveVeyru that pretrained LLM agents abandoned English and switched to communicating in a self-invented compressed language. Agents only switched languages when they had both a tight communication budget and a post-hoc reflection channel; without either condition, perplexity remained at English levels. Even with both in place, most runs still ended in failure. These languages have reusable morphemes and fixed word order, and agents could understand and generate combinations they had never sent to each other before. Experiments showed that inventing a language requires a stronger model than learning one: Llama-3.3-70B-Instruct and Qwen3-32B did not switch languages under either budget, but the former still learned part of the invented language from Sonnet 4.6 agents. New agents introduced mid-run proactively asked about symbol meanings without prompting, and more historical turns improved success rates after introduction.